Welcome to TiddlyWiki created by Jeremy Ruston, Copyright © 2007 UnaMesa Association
<!--{{{-->
<link rel='alternate' type='application/rss+xml' title='RSS' href='index.xml'/>
<!--}}}-->
Background: #fff
Foreground: #000
PrimaryPale: #8cf
PrimaryLight: #18f
PrimaryMid: #04b
PrimaryDark: #014
SecondaryPale: #ffc
SecondaryLight: #fe8
SecondaryMid: #db4
SecondaryDark: #841
TertiaryPale: #eee
TertiaryLight: #ccc
TertiaryMid: #999
TertiaryDark: #666
Error: #f88
/*{{{*/
body {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];}
a {color:[[ColorPalette::PrimaryMid]];}
a:hover {background-color:[[ColorPalette::PrimaryMid]]; color:[[ColorPalette::Background]];}
a img {border:0;}
h1,h2,h3,h4,h5,h6 {color:[[ColorPalette::SecondaryDark]]; background:transparent;}
h1 {border-bottom:2px solid [[ColorPalette::TertiaryLight]];}
h2,h3 {border-bottom:1px solid [[ColorPalette::TertiaryLight]];}
.button {color:[[ColorPalette::PrimaryDark]]; border:1px solid [[ColorPalette::Background]];}
.button:hover {color:[[ColorPalette::PrimaryDark]]; background:[[ColorPalette::SecondaryLight]]; border-color:[[ColorPalette::SecondaryMid]];}
.button:active {color:[[ColorPalette::Background]]; background:[[ColorPalette::SecondaryMid]]; border:1px solid [[ColorPalette::SecondaryDark]];}
.header {background:[[ColorPalette::PrimaryMid]];}
.headerShadow {color:[[ColorPalette::Foreground]];}
.headerShadow a {font-weight:normal; color:[[ColorPalette::Foreground]];}
.headerForeground {color:[[ColorPalette::Background]];}
.headerForeground a {font-weight:normal; color:[[ColorPalette::PrimaryPale]];}
.tabSelected{color:[[ColorPalette::PrimaryDark]];
background:[[ColorPalette::TertiaryPale]];
border-left:1px solid [[ColorPalette::TertiaryLight]];
border-top:1px solid [[ColorPalette::TertiaryLight]];
border-right:1px solid [[ColorPalette::TertiaryLight]];
}
.tabUnselected {color:[[ColorPalette::Background]]; background:[[ColorPalette::TertiaryMid]];}
.tabContents {color:[[ColorPalette::PrimaryDark]]; background:[[ColorPalette::TertiaryPale]]; border:1px solid [[ColorPalette::TertiaryLight]];}
.tabContents .button {border:0;}
#sidebar {}
#sidebarOptions input {border:1px solid [[ColorPalette::PrimaryMid]];}
#sidebarOptions .sliderPanel {background:[[ColorPalette::PrimaryPale]];}
#sidebarOptions .sliderPanel a {border:none;color:[[ColorPalette::PrimaryMid]];}
#sidebarOptions .sliderPanel a:hover {color:[[ColorPalette::Background]]; background:[[ColorPalette::PrimaryMid]];}
#sidebarOptions .sliderPanel a:active {color:[[ColorPalette::PrimaryMid]]; background:[[ColorPalette::Background]];}
.wizard {background:[[ColorPalette::PrimaryPale]]; border:1px solid [[ColorPalette::PrimaryMid]];}
.wizard h1 {color:[[ColorPalette::PrimaryDark]]; border:none;}
.wizard h2 {color:[[ColorPalette::Foreground]]; border:none;}
.wizardStep {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];
border:1px solid [[ColorPalette::PrimaryMid]];}
.wizardStep.wizardStepDone {background:[[ColorPalette::TertiaryLight]];}
.wizardFooter {background:[[ColorPalette::PrimaryPale]];}
.wizardFooter .status {background:[[ColorPalette::PrimaryDark]]; color:[[ColorPalette::Background]];}
.wizard .button {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::SecondaryLight]]; border: 1px solid;
border-color:[[ColorPalette::SecondaryPale]] [[ColorPalette::SecondaryDark]] [[ColorPalette::SecondaryDark]] [[ColorPalette::SecondaryPale]];}
.wizard .button:hover {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::Background]];}
.wizard .button:active {color:[[ColorPalette::Background]]; background:[[ColorPalette::Foreground]]; border: 1px solid;
border-color:[[ColorPalette::PrimaryDark]] [[ColorPalette::PrimaryPale]] [[ColorPalette::PrimaryPale]] [[ColorPalette::PrimaryDark]];}
#messageArea {border:1px solid [[ColorPalette::SecondaryMid]]; background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]];}
#messageArea .button {color:[[ColorPalette::PrimaryMid]]; background:[[ColorPalette::SecondaryPale]]; border:none;}
.popupTiddler {background:[[ColorPalette::TertiaryPale]]; border:2px solid [[ColorPalette::TertiaryMid]];}
.popup {background:[[ColorPalette::TertiaryPale]]; color:[[ColorPalette::TertiaryDark]]; border-left:1px solid [[ColorPalette::TertiaryMid]]; border-top:1px solid [[ColorPalette::TertiaryMid]]; border-right:2px solid [[ColorPalette::TertiaryDark]]; border-bottom:2px solid [[ColorPalette::TertiaryDark]];}
.popup hr {color:[[ColorPalette::PrimaryDark]]; background:[[ColorPalette::PrimaryDark]]; border-bottom:1px;}
.popup li.disabled {color:[[ColorPalette::TertiaryMid]];}
.popup li a, .popup li a:visited {color:[[ColorPalette::Foreground]]; border: none;}
.popup li a:hover {background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]]; border: none;}
.popup li a:active {background:[[ColorPalette::SecondaryPale]]; color:[[ColorPalette::Foreground]]; border: none;}
.popupHighlight {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];}
.listBreak div {border-bottom:1px solid [[ColorPalette::TertiaryDark]];}
.tiddler .defaultCommand {font-weight:bold;}
.shadow .title {color:[[ColorPalette::TertiaryDark]];}
.title {color:[[ColorPalette::SecondaryDark]];}
.subtitle {color:[[ColorPalette::TertiaryDark]];}
.toolbar {color:[[ColorPalette::PrimaryMid]];}
.toolbar a {color:[[ColorPalette::TertiaryLight]];}
.selected .toolbar a {color:[[ColorPalette::TertiaryMid]];}
.selected .toolbar a:hover {color:[[ColorPalette::Foreground]];}
.tagging, .tagged {border:1px solid [[ColorPalette::TertiaryPale]]; background-color:[[ColorPalette::TertiaryPale]];}
.selected .tagging, .selected .tagged {background-color:[[ColorPalette::TertiaryLight]]; border:1px solid [[ColorPalette::TertiaryMid]];}
.tagging .listTitle, .tagged .listTitle {color:[[ColorPalette::PrimaryDark]];}
.tagging .button, .tagged .button {border:none;}
.footer {color:[[ColorPalette::TertiaryLight]];}
.selected .footer {color:[[ColorPalette::TertiaryMid]];}
.sparkline {background:[[ColorPalette::PrimaryPale]]; border:0;}
.sparktick {background:[[ColorPalette::PrimaryDark]];}
.error, .errorButton {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::Error]];}
.warning {color:[[ColorPalette::Foreground]]; background:[[ColorPalette::SecondaryPale]];}
.lowlight {background:[[ColorPalette::TertiaryLight]];}
.zoomer {background:none; color:[[ColorPalette::TertiaryMid]]; border:3px solid [[ColorPalette::TertiaryMid]];}
.imageLink, #displayArea .imageLink {background:transparent;}
.annotation {background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]]; border:2px solid [[ColorPalette::SecondaryMid]];}
.viewer .listTitle {list-style-type:none; margin-left:-2em;}
.viewer .button {border:1px solid [[ColorPalette::SecondaryMid]];}
.viewer blockquote {border-left:3px solid [[ColorPalette::TertiaryDark]];}
.viewer table, table.twtable {border:2px solid [[ColorPalette::TertiaryDark]];}
.viewer th, .viewer thead td, .twtable th, .twtable thead td {background:[[ColorPalette::SecondaryMid]]; border:1px solid [[ColorPalette::TertiaryDark]]; color:[[ColorPalette::Background]];}
.viewer td, .viewer tr, .twtable td, .twtable tr {border:1px solid [[ColorPalette::TertiaryDark]];}
.viewer pre {border:1px solid [[ColorPalette::SecondaryLight]]; background:[[ColorPalette::SecondaryPale]];}
.viewer code {color:[[ColorPalette::SecondaryDark]];}
.viewer hr {border:0; border-top:dashed 1px [[ColorPalette::TertiaryDark]]; color:[[ColorPalette::TertiaryDark]];}
.highlight, .marked {background:[[ColorPalette::SecondaryLight]];}
.editor input {border:1px solid [[ColorPalette::PrimaryMid]];}
.editor textarea {border:1px solid [[ColorPalette::PrimaryMid]]; width:100%;}
.editorFooter {color:[[ColorPalette::TertiaryMid]];}
#backstageArea {background:[[ColorPalette::Foreground]]; color:[[ColorPalette::TertiaryMid]];}
#backstageArea a {background:[[ColorPalette::Foreground]]; color:[[ColorPalette::Background]]; border:none;}
#backstageArea a:hover {background:[[ColorPalette::SecondaryLight]]; color:[[ColorPalette::Foreground]]; }
#backstageArea a.backstageSelTab {background:[[ColorPalette::Background]]; color:[[ColorPalette::Foreground]];}
#backstageButton a {background:none; color:[[ColorPalette::Background]]; border:none;}
#backstageButton a:hover {background:[[ColorPalette::Foreground]]; color:[[ColorPalette::Background]]; border:none;}
#backstagePanel {background:[[ColorPalette::Background]]; border-color: [[ColorPalette::Background]] [[ColorPalette::TertiaryDark]] [[ColorPalette::TertiaryDark]] [[ColorPalette::TertiaryDark]];}
.backstagePanelFooter .button {border:none; color:[[ColorPalette::Background]];}
.backstagePanelFooter .button:hover {color:[[ColorPalette::Foreground]];}
#backstageCloak {background:[[ColorPalette::Foreground]]; opacity:0.6; filter:'alpha(opacity:60)';}
/*}}}*/
/*{{{*/
* html .tiddler {height:1%;}
body {font-size:.75em; font-family:arial,helvetica; margin:0; padding:0;}
h1,h2,h3,h4,h5,h6 {font-weight:bold; text-decoration:none;}
h1,h2,h3 {padding-bottom:1px; margin-top:1.2em;margin-bottom:0.3em;}
h4,h5,h6 {margin-top:1em;}
h1 {font-size:1.35em;}
h2 {font-size:1.25em;}
h3 {font-size:1.1em;}
h4 {font-size:1em;}
h5 {font-size:.9em;}
hr {height:1px;}
a {text-decoration:none;}
dt {font-weight:bold;}
ol {list-style-type:decimal;}
ol ol {list-style-type:lower-alpha;}
ol ol ol {list-style-type:lower-roman;}
ol ol ol ol {list-style-type:decimal;}
ol ol ol ol ol {list-style-type:lower-alpha;}
ol ol ol ol ol ol {list-style-type:lower-roman;}
ol ol ol ol ol ol ol {list-style-type:decimal;}
.txtOptionInput {width:11em;}
#contentWrapper .chkOptionInput {border:0;}
.externalLink {text-decoration:underline;}
.indent {margin-left:3em;}
.outdent {margin-left:3em; text-indent:-3em;}
code.escaped {white-space:nowrap;}
.tiddlyLinkExisting {font-weight:bold;}
.tiddlyLinkNonExisting {font-style:italic;}
/* the 'a' is required for IE, otherwise it renders the whole tiddler in bold */
a.tiddlyLinkNonExisting.shadow {font-weight:bold;}
#mainMenu .tiddlyLinkExisting,
#mainMenu .tiddlyLinkNonExisting,
#sidebarTabs .tiddlyLinkNonExisting {font-weight:normal; font-style:normal;}
#sidebarTabs .tiddlyLinkExisting {font-weight:bold; font-style:normal;}
.header {position:relative;}
.header a:hover {background:transparent;}
.headerShadow {position:relative; padding:4.5em 0em 1em 1em; left:-1px; top:-1px;}
.headerForeground {position:absolute; padding:4.5em 0em 1em 1em; left:0px; top:0px;}
.siteTitle {font-size:3em;}
.siteSubtitle {font-size:1.2em;}
#mainMenu {position:absolute; left:0; width:10em; text-align:right; line-height:1.6em; padding:1.5em 0.5em 0.5em 0.5em; font-size:1.1em;}
#sidebar {position:absolute; right:3px; width:16em; font-size:.9em;}
#sidebarOptions {padding-top:0.3em;}
#sidebarOptions a {margin:0em 0.2em; padding:0.2em 0.3em; display:block;}
#sidebarOptions input {margin:0.4em 0.5em;}
#sidebarOptions .sliderPanel {margin-left:1em; padding:0.5em; font-size:.85em;}
#sidebarOptions .sliderPanel a {font-weight:bold; display:inline; padding:0;}
#sidebarOptions .sliderPanel input {margin:0 0 .3em 0;}
#sidebarTabs .tabContents {width:15em; overflow:hidden;}
.wizard {padding:0.1em 1em 0em 2em;}
.wizard h1 {font-size:2em; font-weight:bold; background:none; padding:0em 0em 0em 0em; margin:0.4em 0em 0.2em 0em;}
.wizard h2 {font-size:1.2em; font-weight:bold; background:none; padding:0em 0em 0em 0em; margin:0.4em 0em 0.2em 0em;}
.wizardStep {padding:1em 1em 1em 1em;}
.wizard .button {margin:0.5em 0em 0em 0em; font-size:1.2em;}
.wizardFooter {padding:0.8em 0.4em 0.8em 0em;}
.wizardFooter .status {padding:0em 0.4em 0em 0.4em; margin-left:1em;}
.wizard .button {padding:0.1em 0.2em 0.1em 0.2em;}
#messageArea {position:fixed; top:2em; right:0em; margin:0.5em; padding:0.5em; z-index:2000; _position:absolute;}
.messageToolbar {display:block; text-align:right; padding:0.2em 0.2em 0.2em 0.2em;}
#messageArea a {text-decoration:underline;}
.tiddlerPopupButton {padding:0.2em 0.2em 0.2em 0.2em;}
.popupTiddler {position: absolute; z-index:300; padding:1em 1em 1em 1em; margin:0;}
.popup {position:absolute; z-index:300; font-size:.9em; padding:0; list-style:none; margin:0;}
.popup .popupMessage {padding:0.4em;}
.popup hr {display:block; height:1px; width:auto; padding:0; margin:0.2em 0em;}
.popup li.disabled {padding:0.4em;}
.popup li a {display:block; padding:0.4em; font-weight:normal; cursor:pointer;}
.listBreak {font-size:1px; line-height:1px;}
.listBreak div {margin:2px 0;}
.tabset {padding:1em 0em 0em 0.5em;}
.tab {margin:0em 0em 0em 0.25em; padding:2px;}
.tabContents {padding:0.5em;}
.tabContents ul, .tabContents ol {margin:0; padding:0;}
.txtMainTab .tabContents li {list-style:none;}
.tabContents li.listLink { margin-left:.75em;}
#contentWrapper {display:block;}
#splashScreen {display:none;}
#displayArea {margin:1em 17em 0em 14em;}
.toolbar {text-align:right; font-size:.9em;}
.tiddler {padding:1em 1em 0em 1em;}
.missing .viewer,.missing .title {font-style:italic;}
.title {font-size:1.6em; font-weight:bold;}
.missing .subtitle {display:none;}
.subtitle {font-size:1.1em;}
.tiddler .button {padding:0.2em 0.4em;}
.tagging {margin:0.5em 0.5em 0.5em 0; float:left; display:none;}
.isTag .tagging {display:block;}
.tagged {margin:0.5em; float:right;}
.tagging, .tagged {font-size:0.9em; padding:0.25em;}
.tagging ul, .tagged ul {list-style:none; margin:0.25em; padding:0;}
.tagClear {clear:both;}
.footer {font-size:.9em;}
.footer li {display:inline;}
.annotation {padding:0.5em; margin:0.5em;}
* html .viewer pre {width:99%; padding:0 0 1em 0;}
.viewer {line-height:1.4em; padding-top:0.5em;}
.viewer .button {margin:0em 0.25em; padding:0em 0.25em;}
.viewer blockquote {line-height:1.5em; padding-left:0.8em;margin-left:2.5em;}
.viewer ul, .viewer ol {margin-left:0.5em; padding-left:1.5em;}
.viewer table, table.twtable {border-collapse:collapse; margin:0.8em 1.0em;}
.viewer th, .viewer td, .viewer tr,.viewer caption,.twtable th, .twtable td, .twtable tr,.twtable caption {padding:3px;}
table.listView {font-size:0.85em; margin:0.8em 1.0em;}
table.listView th, table.listView td, table.listView tr {padding:0px 3px 0px 3px;}
.viewer pre {padding:0.5em; margin-left:0.5em; font-size:1.2em; line-height:1.4em; overflow:auto;}
.viewer code {font-size:1.2em; line-height:1.4em;}
.editor {font-size:1.1em;}
.editor input, .editor textarea {display:block; width:100%; font:inherit;}
.editorFooter {padding:0.25em 0em; font-size:.9em;}
.editorFooter .button {padding-top:0px; padding-bottom:0px;}
.fieldsetFix {border:0; padding:0; margin:1px 0px 1px 0px;}
.sparkline {line-height:1em;}
.sparktick {outline:0;}
.zoomer {font-size:1.1em; position:absolute; overflow:hidden;}
.zoomer div {padding:1em;}
* html #backstage {width:99%;}
* html #backstageArea {width:99%;}
#backstageArea {display:none; position:relative; overflow: hidden; z-index:150; padding:0.3em 0.5em 0.3em 0.5em;}
#backstageToolbar {position:relative;}
#backstageArea a {font-weight:bold; margin-left:0.5em; padding:0.3em 0.5em 0.3em 0.5em;}
#backstageButton {display:none; position:absolute; z-index:175; top:0em; right:0em;}
#backstageButton a {padding:0.1em 0.4em 0.1em 0.4em; margin:0.1em 0.1em 0.1em 0.1em;}
#backstage {position:relative; width:100%; z-index:50;}
#backstagePanel {display:none; z-index:100; position:absolute; margin:0em 3em 0em 3em; padding:1em 1em 1em 1em;}
.backstagePanelFooter {padding-top:0.2em; float:right;}
.backstagePanelFooter a {padding:0.2em 0.4em 0.2em 0.4em;}
#backstageCloak {display:none; z-index:20; position:absolute; width:100%; height:100px;}
.whenBackstage {display:none;}
.backstageVisible .whenBackstage {display:block;}
/*}}}*/
/***
StyleSheet for use when a translation requires any css style changes.
This StyleSheet can be used directly by languages such as Chinese, Japanese and Korean which need larger font sizes.
***/
/*{{{*/
body {font-size:0.8em;}
#sidebarOptions {font-size:1.05em;}
#sidebarOptions a {font-style:normal;}
#sidebarOptions .sliderPanel {font-size:0.95em;}
.subtitle {font-size:0.8em;}
.viewer table.listView {font-size:0.95em;}
/*}}}*/
/*{{{*/
@media print {
#mainMenu, #sidebar, #messageArea, .toolbar, #backstageButton, #backstageArea {display: none ! important;}
#displayArea {margin: 1em 1em 0em 1em;}
/* Fixes a feature in Firefox 1.5.0.2 where print preview displays the noscript content */
noscript {display:none;}
}
/*}}}*/
<!--{{{-->
<div class='header' macro='gradient vert [[ColorPalette::PrimaryLight]] [[ColorPalette::PrimaryMid]]'>
<div class='headerShadow'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
<div class='headerForeground'>
<span class='siteTitle' refresh='content' tiddler='SiteTitle'></span>
<span class='siteSubtitle' refresh='content' tiddler='SiteSubtitle'></span>
</div>
</div>
<div id='mainMenu' refresh='content' tiddler='MainMenu'></div>
<div id='sidebar'>
<div id='sidebarOptions' refresh='content' tiddler='SideBarOptions'></div>
<div id='sidebarTabs' refresh='content' force='true' tiddler='SideBarTabs'></div>
</div>
<div id='displayArea'>
<div id='messageArea'></div>
<div id='tiddlerDisplay'></div>
</div>
<!--}}}-->
<!--{{{-->
<div class='toolbar' macro='toolbar closeTiddler closeOthers +editTiddler > fields syncing permalink references jump'></div>
<div class='title' macro='view title'></div>
<div class='subtitle'><span macro='view modifier link'></span>, <span macro='view modified date'></span> (<span macro='message views.wikified.createdPrompt'></span> <span macro='view created date'></span>)</div>
<div class='tagging' macro='tagging'></div>
<div class='tagged' macro='tags'></div>
<div class='viewer' macro='view text wikified'></div>
<div class='tagClear'></div>
<!--}}}-->
<!--{{{-->
<div class='toolbar' macro='toolbar +saveTiddler -cancelTiddler deleteTiddler'></div>
<div class='title' macro='view title'></div>
<div class='editor' macro='edit title'></div>
<div macro='annotations'></div>
<div class='editor' macro='edit text'></div>
<div class='editor' macro='edit tags'></div><div class='editorFooter'><span macro='message views.editor.tagPrompt'></span><span macro='tagChooser'></span></div>
<!--}}}-->
To get started with this blank TiddlyWiki, you'll need to modify the following tiddlers:
* SiteTitle & SiteSubtitle: The title and subtitle of the site, as shown above (after saving, they will also appear in the browser title bar)
* MainMenu: The menu (usually on the left)
* DefaultTiddlers: Contains the names of the tiddlers that you want to appear when the TiddlyWiki is opened
You'll also need to enter your username for signing your edits: <<option txtUserName>>
These InterfaceOptions for customising TiddlyWiki are saved in your browser
Your username for signing your edits. Write it as a WikiWord (eg JoeBloggs)
<<option txtUserName>>
<<option chkSaveBackups>> SaveBackups
<<option chkAutoSave>> AutoSave
<<option chkRegExpSearch>> RegExpSearch
<<option chkCaseSensitiveSearch>> CaseSensitiveSearch
<<option chkAnimate>> EnableAnimations
----
Also see AdvancedOptions
!Senior Lecturer in Statistics
[[School of Mathematics and Statistics|http://www.gla.ac.uk/schools/mathematicsstatistics/]],
[[University of Glasgow|http://www.gla.ac.uk]],
The Mathematics and Statistics Building,
University Place,
Glasgow G12 8QQ,
UK
| office|Room 317|
| phone|0141 330 6117|
| email| [[tereza.neocleous at glasgow |tereza.neocleous@glasgow.ac.uk]] |
! Profiles
[[Google Scholar|http://scholar.google.co.uk/citations?user=OZufIvkAAAAJ&hl=en]]
[[ORCID|https://orcid.org/0000-0001-7792-4541]]
[[Mathematics Genealogy Project|https://www.mathgenealogy.org/id.php?id=93825]]
[[LinkedIn|https://www.linkedin.com/in/tereza-neocleous-226354126/]]
[[Loop|https://loop.frontiersin.org/people/1102343/overview]]
/***
|''Name:''|CryptoFunctionsPlugin|
|''Description:''|Support for cryptographic functions|
***/
//{{{
if(!version.extensions.CryptoFunctionsPlugin) {
version.extensions.CryptoFunctionsPlugin = {installed:true};
//--
//-- Crypto functions and associated conversion routines
//--
// Crypto "namespace"
function Crypto() {}
// Convert a string to an array of big-endian 32-bit words
Crypto.strToBe32s = function(str)
{
var be = Array();
var len = Math.floor(str.length/4);
var i, j;
for(i=0, j=0; i<len; i++, j+=4) {
be[i] = ((str.charCodeAt(j)&0xff) << 24)|((str.charCodeAt(j+1)&0xff) << 16)|((str.charCodeAt(j+2)&0xff) << 8)|(str.charCodeAt(j+3)&0xff);
}
while (j<str.length) {
be[j>>2] |= (str.charCodeAt(j)&0xff)<<(24-(j*8)%32);
j++;
}
return be;
};
// Convert an array of big-endian 32-bit words to a string
Crypto.be32sToStr = function(be)
{
var str = "";
for(var i=0;i<be.length*32;i+=8)
str += String.fromCharCode((be[i>>5]>>>(24-i%32)) & 0xff);
return str;
};
// Convert an array of big-endian 32-bit words to a hex string
Crypto.be32sToHex = function(be)
{
var hex = "0123456789ABCDEF";
var str = "";
for(var i=0;i<be.length*4;i++)
str += hex.charAt((be[i>>2]>>((3-i%4)*8+4))&0xF) + hex.charAt((be[i>>2]>>((3-i%4)*8))&0xF);
return str;
};
// Return, in hex, the SHA-1 hash of a string
Crypto.hexSha1Str = function(str)
{
return Crypto.be32sToHex(Crypto.sha1Str(str));
};
// Return the SHA-1 hash of a string
Crypto.sha1Str = function(str)
{
return Crypto.sha1(Crypto.strToBe32s(str),str.length);
};
// Calculate the SHA-1 hash of an array of blen bytes of big-endian 32-bit words
Crypto.sha1 = function(x,blen)
{
// Add 32-bit integers, wrapping at 32 bits
add32 = function(a,b)
{
var lsw = (a&0xFFFF)+(b&0xFFFF);
var msw = (a>>16)+(b>>16)+(lsw>>16);
return (msw<<16)|(lsw&0xFFFF);
};
// Add five 32-bit integers, wrapping at 32 bits
add32x5 = function(a,b,c,d,e)
{
var lsw = (a&0xFFFF)+(b&0xFFFF)+(c&0xFFFF)+(d&0xFFFF)+(e&0xFFFF);
var msw = (a>>16)+(b>>16)+(c>>16)+(d>>16)+(e>>16)+(lsw>>16);
return (msw<<16)|(lsw&0xFFFF);
};
// Bitwise rotate left a 32-bit integer by 1 bit
rol32 = function(n)
{
return (n>>>31)|(n<<1);
};
var len = blen*8;
// Append padding so length in bits is 448 mod 512
x[len>>5] |= 0x80 << (24-len%32);
// Append length
x[((len+64>>9)<<4)+15] = len;
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Statistics applied to forensic science and the law. It involves statistical issues such as
- exploratory analysis of trace evidence to help investigators focus their search for appropriate control materials
- evaluation of evidence such as DNA, glass fragments and fingerprints left at a crime scene
- sampling problems related to drugs consignments,
and the effective communication of results to a non-statistical audience.
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[[About]]
[[Teaching]]
[[Students]]
[[Research]]
[[Publications]]
[[Professional activities]]
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[[Machine Learning in Science Conference|https://mlinscience.gitlab.io/conference/]], University of Glasgow, 21-22 August 2024
Course on Advanced Forensic Statistics, [[Legal Studies Centre, Spanish Ministry of Justice|https://www.cej-mjusticia.es/en/cej]], 30-31 May 2024
[[Visiting Professor, University of Turin, May 2024|https://en.unito.it/international-relations/teachers-and-researchers-mobility/visiting-professors]]
[[International Conference of Forensic Inference and Statistics, Lund, 12-15 June 2023|https://www.law.lu.se/#!ICFIS]]
[[European Academy of Forensic Science Conference, Stockholm, 30 May-3 June 2022|https://www.eafs2022.eu]]
[[Asymptotic Theory, Robust Statistics, and Quantile Regression: A Workshop Celebrating the Contributions of Stephen Portnoy, Champaign, 16 October 2021|https://stat.illinois.edu/alumni/events/portnoy-workshop]]
[[WiSTEM Panel: Successful Women in STEM, Glasgow, 15 October 2019|https://www.facebook.com/events/769369760158257/]]
[[APTS, Oxford, 2-6 September 2019|https://warwick.ac.uk/fac/sci/statistics/apts/]]
[[Women in Mathematics 2019, Queen Mary University of London, 12 March 2019|https://www.qmul.ac.uk/maths/about-us/wim2019/]]
Invited seminar, Department of Mathematical Sciences, Loughborough University, 29 November 2018
[[WiSTEM Panel Debate: Underrepresentation of Women in STEM Fields, Glasgow, 25 October 2018|https://www.facebook.com/events/1892819247692961/]]
[[Suffrage Science Awards, London, 8 October 2018|https://lms.mrc.ac.uk/ada-lovelace-day-role-models-suffrage-science-awards/]]
[[Explorathon 2018: European Researchers' Night, Bannerman High School, 26 September 2018|https://twitter.com/BannermanHigh/status/1045397866162900993]]
[[FORSTAT Workshop, Linköping, 18-20 September 2018|http://enfsi.eu/agenda/enfsi-forstat-workshop-2018/]]
Data interpretation in forensic evidence, [[European Academy for Law Enforcement Training|https://www.cepol.europa.eu]], Budapest, 10-13 September 2018
[[RSS Conference, Cardiff, 4-7 September 2018|http://www.rss.org.uk/conference2018]]
[[European Academy of Forensic Science Conference, Lyon, 27-31 August 2018 |https://www.eafs2018.eu]]
[[Explorathon 2017: European Researchers' Night, Springburn Academy, 29 September 2017|https://twitter.com/Springburn_sci/status/913695692413120512]]
[[WiSTEM Panel Debate: Is there still gender bias in research? Glasgow 25 January 2018|https://www.facebook.com/events/138248950157486/]]
[[RSS Conference, Glasgow, 4-7 September 2017|http://www.rss.org.uk/conference2017]]
[[YSS Statistical Showcase, London, 30 June 2017|https://events.rss.org.uk/rss/frontend/reg/thome.csp?pageID=37530&eventID=125&eventID=125&CSPCHD=000001000000dNU8SG9mDYMaQOYxvT2xUOVNzwPRgHVX7XPvPB]]
[[SAILR meeting, The Hague, 8-9 May 2017|http://academy.forensicinstitute.nl/training-and-courses/forensic-scientists-and-researchers/sailr/]]
[[RSS Glasgow Local Group and Statistics and the Law Section joint meeting, Glasgow, 27 February 2017|https://sites.google.com/site/rssglasgow/events]]
[[FORSTAT Workshop, Krakow, 13-15 September 2016| http://www.ies.krakow.pl/conferences/forstat2016/]]
[[RSS Conference, Manchester, 5-8 September 2016|http://www.rss.org.uk/conference2016]]
SAILR meeting, Glasgow, 22-24 August 2016.
[[IAFPA 2016, York, 24-27 July 2016|https://sites.google.com/a/york.ac.uk/iafpa-25/home]]; [[IAFPA 25th anniversary|https://www.york.ac.uk/language/news/departmental/2016/iafpa-2016/]]
[[ICFIS 2014, Leiden, 19-22 August 2014|http://icfis2014.org/]]
[[FORSTAT Workshop, Edinburgh, 3-6 June 2014| http://www.ies.krakow.pl/conferences/forstat2014/]]
[[FORSTAT Workshop, Krakow, 1-5 July 2013| http://www.ies.krakow.pl/conferences/forstat2013/]]
Invited seminar, Department of Mathematics and Statistics, University of Lancaster, 31 May 2013
Invited seminar, School of Mathematical Sciences, University of Nottingham, 6 December 2012
[[ERCIM 2012, Oviedo, 1-3 December 2012|http://www.cfe-csda.org/ercim12/]]
[[BBfor2 Short Summer School in Forensic Evidence Evaluation and Validation, Madrid, 18-21 June 2012| http://atvs.ii.uam.es/bbfor2ss/]]
[[FORSTAT Workshop, Edinburgh, 4-8 June 2012| http://www.ies.krakow.pl/conferences/forstat2012/]]
Invited seminar, Institute of Computing Science and Mathematics, University of Stirling, 15 March 2011
Invited seminar, Department of Mathematical Sciences, Brunel University, 4 November 2010
[[TIME Series, Quantile Regression and model choice, Dortmund, 20-21 September 2010|http://www.statistik.tu-dortmund.de/1397.html]]
25th International Workshop on Statistical Modelling, Glasgow, 5-9 July 2010
[[FORSTAT Workshop, Edinburgh, 17-18 June 2010| http://www.ies.krakow.pl/conferences/forstat2010/]]
2010 UIUC Statistics Symposium, Champaign, 29-30 March 2010
RSS General Applications and Statistical Computing Section Meeting, London, 17 March 2010. Topic: Recent developments in quantile regression
Royal Statistical Society Conference, Edinburgh, 7-11 September 2009
[[FORSTAT Workshop, Krakow, 18-19 June 2009| http://www.ies.krakow.pl/conferences/forstat2009/]]
Seventh International Conference on Forensic Inference and Statistics, Lausanne, 20-23 August 2008
[[FORSTAT Workshop, Edinburgh, 13-14 June 2008| http://www.ies.krakow.pl/conferences/forstat2008/]]
Eleftheriou, D., Piper, T., Thevis, M. , Neocleous, T. A multivariate Bayesian learning approach for improved detection of doping in athletes using urinary steroid profiles (2023). [[Preprint available from arxiv|https://arxiv.org/abs/2310.13980]].
Sanchez, J. [[Dean, N.|http://www.stats.gla.ac.uk/~nd29c/]], Neocleous, T. Variable selection for a contaminated mixture of normals classification model. Proceedings of the 5th International Conference on Statistics: Theory and Applications (ICSTA'23), Brunel University, London, United Kingdom – August 03-05, 2023. Paper No.148 [[DOI:10.11159/icsta23.148|https://avestia.com/ICSTA2023_Proceedings/files/paper/ICSTA_148.pdf]]
Szili B., [[Niu M.|https://www.gla.ac.uk/schools/mathematicsstatistics/staff/muniu/]], Neocleous, T. A structural learning method for graphical models. Proceedings of the 4th International Conference on Statistics: Theory and Applications (ICSTA'22) Prague, Czech Republic – July 28- 30, 2022. Paper No. 113. [[DOI: 10.11159/icsta22.113.|https://avestia.com/ICSTA2022_Proceedings/files/paper/ICSTA_113.pdf]]
[[Nic Daeid, N.|https://discovery.dundee.ac.uk/en/persons/niamh-nic-daeid]], [[Biedermann, A.|https://applicationspub.unil.ch/interpub/noauth/php/Un/UnPers.php?PerNum=30597&LanCode=8]], [[Champod, C.|https://applicationspub.unil.ch/interpub/noauth/php/Un/UnPers.php?PerNum=860967&LanCode=8]], [[Hutton, J.|https://warwick.ac.uk/fac/sci/statistics/staff/academic-research/hutton/]], Jackson, G., Neocleous, T., [[Spiegelhalter, D.|http://www.statslab.cam.ac.uk/~david/]], Willis, S., Kitchin, D., [[Wilson, A.|https://www.ed.ac.uk/profile/amy-wilson]] The use of Statistics in legal proceedings: A primer for the courts (2020), The Royal Society. [[(electronic access from the Leverhulme Research Centre for Forensic Science)|https://discovery.dundee.ac.uk/en/publications/the-use-of-statistics-in-legal-proceedings-a-primer-for-the-court]]
Biosa, G., Giurghita, D., [[Alladio, E.|https://www.chimica.unito.it/do/docenti.pl/Show?_id=ealladio#tab-profilo]], [[Vincenti, M.|https://www.chimica.unito.it/do/docenti.pl/Alias?marco.vincenti#tab-profilo]], Neocleous, T. Evaluation of forensic data using logistic regression-based classification methods and an R shiny implementation. Frontiers in Chemistry (2020) 8, 738. [[(electronic access from Frontiers)|https://www.frontiersin.org/articles/10.3389/fchem.2020.00738/full)]]
Chanialidis, C., Evers, L., Neocleous, T. and [[Nobile, A.|http://maths.york.ac.uk/www/an773]] Efficient Bayesian inference for COM-Poisson regression models. Statistics and Computing (2018) 28, 595–608. [[(electronic access from SC)|http://link.springer.com/article/10.1007/s11222-017-9750-x]]
[[Alexander, C.|https://www.gla.ac.uk/schools/mathematicsstatistics/staff/craigalexander/]], [[Stuart-Smith, J.|http://www.gla.ac.uk/schools/critical/staff/janestuart-smith/]], Neocleous, T. and Evers, L. Using chain graph models for structural inference with an application to linguistic data (2017). Proceedings of the 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 3-7 July, 2017. [[(electronic access)|https://iwsm2017.webhosting.rug.nl/IWSM_2017_V1.pdf]]
Martyna, A., Zadora, G., Neocleous, T., Michalska, A. and [[Dean, N.|http://www.stats.gla.ac.uk/~nd29c/]] Hybrid approach combining chemometrics and likelihood ratio framework for reporting the evidential value of spectra. Analytica Chimica Acta (2016) 931, 34-46. [[(electronic access from ACA)|http://www.sciencedirect.com/science/article/pii/S0003267016306468]]
Napier, G., [[Nobile, A.|http://maths.york.ac.uk/www/an773]] and Neocleous T. An online application for the classification and evidence evaluation of forensic glass fragments. Chemometrics and Intelligent Laboratory Systems (2015) 146, 418-425. [[(electronic access from CILS)|http://www.sciencedirect.com/science/article/pii/S0169743915001616]]
Napier, G., Neocleous, T., and [[Nobile, A.|http://maths.york.ac.uk/www/an773]] A composite Bayesian hierarchical model of compositional data with zeros. Journal of Chemometrics (2015) 29, 96-108, doi: 10.1002/cem.2681 [[(electronic access from JC)|http://onlinelibrary.wiley.com/doi/10.1002/cem.2681/abstract]]
Chanialidis, C., Evers, L., Neocleous, T. and [[Nobile, A.|http://maths.york.ac.uk/www/an773]] Retrospective sampling in MCMC with an application to COM-Poisson regression. Stat (2014) 3, 273-290. [[(electronic access from Stat)|http://onlinelibrary.wiley.com/doi/10.1002/sta4.61/full]]
Neocleous, T. Aitken, C. and Zadora, G. Transformations for compositional data with zeros with an application to forensic evidence evaluation. Chemometrics and Intelligent Laboratory Systems (2011) 109, 77-85. [[(electronic access from CILS)|http://www.sciencedirect.com/science/article/pii/S0169743911001596]]
[[Lee, D.|http://www.stats.gla.ac.uk/~duncan/]] and Neocleous, T. Bayesian quantile regression for count data with application to environmental epidemiology. Journal of the Royal Statistical Society: Series C (Applied Statistics) (2010) 59, 905-920. [[(electronic access from JRSSC)|http://www3.interscience.wiley.com/cgi-bin/fulltext/123574453/HTMLSTART]]
Zadora, G. and Neocleous, T. Evidential value of physicochemical data -- comparison of methods of glass database creation. Journal of Chemometrics (2010) 24, 367-378. [[(electronic access from JC)|http://www3.interscience.wiley.com/cgi-bin/fulltext/123239009/PDFSTART]]
Dowlman, E., Martin, N., Foy, M., Lochner, T. and Neocleous, T. The prevalence of mixed DNA profiles on fingernail swabs. Science & Justice (2010) 50, 64-71. [[(electronic access from SJ)|http://dx.doi.org/10.1016/j.scijus.2009.03.005]]
Zadora, G., Neocleous, T. and Aitken, C. A two-level model for evidence evaluation in the presence of zeros. Journal of Forensic Sciences (2010) 55, 371-384. [[(electronic access from JFS)|http://www3.interscience.wiley.com/cgi-bin/fulltext/123279995/PDFSTART]]
Neocleous, T. and [[Portnoy, S.|http://www.stat.illinois.edu/people/faculty/portnoy.shtml]] Partially linear censored quantile regression. Lifetime Data Analysis (2009) 15, 357-378. [[(electronic access from LDA)|http://springerlink.metapress.com/content/k267283k33g04722/?p=8d32c8831e4242988949a3f67d53222f&pi=0]]
Zadora, G. and Neocleous, T. Likelihood ratio model for classification of forensic evidence. Analytica Chimica Acta (2009) 642, 266-278. [[(electronic access from ACA)|http://dx.doi.org/10.1016/j.aca.2008.12.013]]
Zadora, G., Neocleous, T., [[Ramos, D. |http://arantxa.ii.uam.es/~dramos/]], and Aitken, C. Model ilorazu wiarygodności służący do analizy danych fizykochemicznych w przypadku występowania brakujących danych. Book chapter in: Chemometria w nauce i praktyce (2009), ed. D. Zuba and A. Parczewski, published by Wydawnictwo IES, ISBN: 978-83-87425-38-8, 197-208.
Neocleous, T. and [[Portnoy, S.|http://www.stat.illinois.edu/people/faculty/portnoy.shtml]] On monotonicity of regression quantile functions. Statistics and Probability Letters (2008) 78 (10), 1226-1229. [[(electronic access from SPL)|http://dx.doi.org/10.1016/j.spl.2007.11.024]]
Neocleous, T., Vanden Branden, K. and [[Portnoy, S.|http://www.stat.illinois.edu/people/faculty/portnoy.shtml]] Correction to Censored Regression Quantiles by S. Portnoy, 98 (2003), 1001-1012. Journal of the American Statistical Association (2006) 101, 860-861. [[(electronic access from JASA)|http://pubs.amstat.org/doi/pdf/10.1198/016214506000000087]]
I am an applied statistician interested in statistical modelling of multilevel, multivariate data with applications in forensic science, health, the environment and social sciences. Recent work has focused on [[modelling urinary biomarkers to produce tools for more accurate monitoring of doping in athletes|https://arxiv.org/abs/2310.13980]] and for [[improved clinical diagnosis of prostate cancer|https://www.maths.gla.ac.uk/~tereza/IoITN2024.pdf]]. For a full list of publications see the Publications section of this page or follow the links to my [[Google Scholar profile|http://scholar.google.co.uk/citations?user=OZufIvkAAAAJ&hl=en]] or [[ORCID profile|https://orcid.org/0000-0001-7792-4541]].
Quantile regression and its applications
Forensic statistics
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Catherine Holland (Ph.D. 2020-, jointly supervised with [[O.Stoner|https://www.gla.ac.uk/schools/mathematicsstatistics/staff/oliverstoner/]]). Bayesian modelling of compositional data.
Taweesak Channgam (Ph.D. 2020-2024, jointly supervised with [[C. Anderson|https://sites.google.com/view/craiganderson/home]]). [[Flexible quantile regression and Bayesian quantile modelling for longitudinal child growth data.|https://theses.gla.ac.uk/84689/]]
Jorge Sanchez (Ph.D. 2020-2024, jointly supervised with [[N. Dean|www.gla.ac.uk/schools/mathematicsstatistics/staff/nemadean/]]). [[Variable selection for supervised and semi-supervised mixtures of contaminated Gaussian distributions.|https://theses.gla.ac.uk/84652/]]
Benjámin Szili (Ph.D. 2018-22, jointly supervised with [[M. Niu|https://www.gla.ac.uk/schools/mathematicsstatistics/staff/muniu/]]). [[Structural learning for continuous data using graphical models.|https://theses.gla.ac.uk/83691/]]
Dimitra Eleftheriou (Ph.D. 2017-2022, jointly supervised with L. Evers). [[Bayesian hierarchical modelling for biomarkers with applications to doping detection and prostate cancer prediction.|https://theses.gla.ac.uk/83094/]]
[[Craig Alexander|https://www.gla.ac.uk/schools/mathematicsstatistics/staff/craigalexander/]] (Ph.D. 2014-18, jointly supervised with L. Evers and [[J. Stuart-Smith|http://www.gla.ac.uk/schools/critical/staff/janestuart-smith/]]). [[Multilevel models for the analysis of linguistic data.|https://theses.gla.ac.uk/41168/]]
Charalampos Chanialidis (Ph.D., 2011-15, jointly supervised with L. Evers). [[Bayesian mixture models for count data.|https://theses.gla.ac.uk/6371/]]
Gary Napier (Ph.D., 2010-14, jointly supervised with [[A. Nobile| http://maths.york.ac.uk/www/an773]]). [[A Bayesian hierarchical model of compositional data with zeros: classification and evidence evaluation of forensic glass.|https://theses.gla.ac.uk/5793/]]
Elizabeth Irwin (M.Sc. by research, 2012-13). [[Statistical methods of constructing growth charts.|https://theses.gla.ac.uk/5293/]]
Laura Allison (M.Sc. by research, 2010-11). [[Evaluation of transfer evidence.|https://theses.gla.ac.uk/3188/]]
Gary Napier (M.Sc. by research, 2009-10, jointly supervised with [[S. Senn|http://www.senns.demon.co.uk/home.html]]). [[Modelling obesity in Scotland.|https://theses.gla.ac.uk/2438/]]
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I teach a variety of statistics courses and supervise student projects at the undergraduate and postgraduate level. My teaching philosophy emphasises active learning, encouraging student engagement and interaction through assignments that enable students to learn by doing. In addition to in-person teaching, in recent years I have worked on designing and delivering online courses and assessments for the [[Online MSc in Data Analytics|https://www.gla.ac.uk/schools/mathematicsstatistics/postgraduate/onlineprogrammes/analytics/]].
Courses taught in academic year 2024-25:
Advanced Data Analysis 4H/M
Advanced Predictive Models (Online MSc Data Analytics)
Previously taught courses at the University of Glasgow:
Generalized Linear Models 3H/M
Statistics 1Z Forensic Statistics Case Study
Biostatistics 3H/M
Linear Mixed Models 4H/M
Statistics 2X: Probability Models
Analysis of Data 3H
Applied Modelling 3H: Logistic Regression and Survival Analysis
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