Jump to content
Change search PrimeFaces.cw("Fieldset","widget_formSmash_search",{id:"formSmash:search",widgetVar:"widget_formSmash_search",toggleable:true,collapsed:true,toggleSpeed:500,behaviors:{toggle:function(ext) {PrimeFaces.ab({s:"formSmash:search",e:"toggle",f:"formSmash",p:"formSmash:search"},ext);}}});
$(function(){PrimeFaces.cw("Dialog","citationDialog",{id:"formSmash:upper:j_idt183",widgetVar:"citationDialog",width:"800",height:"600"});});
$(function(){PrimeFaces.cw("ImageSwitch","widget_formSmash_j_idt964",{id:"formSmash:j_idt964",widgetVar:"widget_formSmash_j_idt964",fx:"fade",speed:500,timeout:8000},"imageswitch");});
#### Open Access in DiVA

####

#### Authority records

Abramowicz, Konrad
#### Search in DiVA

##### By author/editor

Abramowicz, Konrad
##### By organisation

Department of Mathematics and Mathematical Statistics
On the subject

Probability Theory and Statistics
#### Search outside of DiVA

GoogleGoogle Scholar$(function(){PrimeFaces.cw('Chart','widget_formSmash_j_idt1150_0_downloads',{id:'formSmash:j_idt1150:0:downloads',type:'bar',responsive:true,data:[[6,7,4,2,7,12,27,6,14,1]],title:"Downloads of File (FULLTEXT01)",axes:{xaxis: {label:"",renderer:$.jqplot.CategoryAxisRenderer,tickOptions:{angle:-90}},yaxis: {label:"",min:0,max:30,renderer:$.jqplot.LinearAxisRenderer,tickOptions:{angle:0}}},series:[{label:'diva2:437283'}],ticks:["Nov -23","Dec -23","Jan -24","Feb -24","Mar -24","Apr -24","May -24","Jun -24","Jul -24","Aug -24"],orientation:"vertical",barMargin:3,datatip:true,datatipFormat:"<span style=\"display:none;\">%2$d</span><span>%2$d</span>"},'charts');}); Total: 1800 downloads$(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_j_idt1153",{id:"formSmash:j_idt1153",widgetVar:"widget_formSmash_j_idt1153",target:"formSmash:downloadLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade"});}); findCitings = function() {PrimeFaces.ab({s:"formSmash:j_idt1155",f:"formSmash",u:"formSmash:citings",pa:arguments[0]});};$(function() {findCitings();}); $(function(){PrimeFaces.cw('Chart','widget_formSmash_visits',{id:'formSmash:visits',type:'bar',responsive:true,data:[[21,27,8,17,19,23,37,9,16,2]],title:"Visits for this publication",axes:{xaxis: {label:"",renderer:$.jqplot.CategoryAxisRenderer,tickOptions:{angle:-90}},yaxis: {label:"",min:0,max:40,renderer:$.jqplot.LinearAxisRenderer,tickOptions:{angle:0}}},series:[{label:'diva2:437283'}],ticks:["Nov -23","Dec -23","Jan -24","Feb -24","Mar -24","Apr -24","May -24","Jun -24","Jul -24","Aug -24"],orientation:"vertical",barMargin:3,datatip:true,datatipFormat:"<span style=\"display:none;\">%2$d</span><span>%2$d</span>"},'charts');}); Total: 4367 hits
$(function(){PrimeFaces.cw("Dialog","citationDialog",{id:"formSmash:lower:j_idt1248",widgetVar:"citationDialog",width:"800",height:"600"});});

CiteExport$(function(){PrimeFaces.cw("TieredMenu","widget_formSmash_upper_j_idt165",{id:"formSmash:upper:j_idt165",widgetVar:"widget_formSmash_upper_j_idt165",autoDisplay:true,overlay:true,my:"left top",at:"left bottom",trigger:"formSmash:upper:exportLink",triggerEvent:"click"});}); $(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_upper_j_idt166_j_idt168",{id:"formSmash:upper:j_idt166:j_idt168",widgetVar:"widget_formSmash_upper_j_idt166_j_idt168",target:"formSmash:upper:j_idt166:permLink",showEffect:"blind",hideEffect:"fade",my:"right top",at:"right bottom",showCloseIcon:true});});

Numerical analysis for random processes and fields and related design problemsPrimeFaces.cw("AccordionPanel","widget_formSmash_some",{id:"formSmash:some",widgetVar:"widget_formSmash_some",multiple:true}); PrimeFaces.cw("AccordionPanel","widget_formSmash_all",{id:"formSmash:all",widgetVar:"widget_formSmash_all",multiple:true});
function selectAll()
{
var panelSome = $(PrimeFaces.escapeClientId("formSmash:some"));
var panelAll = $(PrimeFaces.escapeClientId("formSmash:all"));
panelAll.toggle();
toggleList(panelSome.get(0).childNodes, panelAll);
toggleList(panelAll.get(0).childNodes, panelAll);
}
/*Toggling the list of authorPanel nodes according to the toggling of the closeable second panel */
function toggleList(childList, panel)
{
var panelWasOpen = (panel.get(0).style.display == 'none');
// console.log('panel was open ' + panelWasOpen);
for (var c = 0; c < childList.length; c++) {
if (childList[c].classList.contains('authorPanel')) {
clickNode(panelWasOpen, childList[c]);
}
}
}
/*nodes have styleClass ui-corner-top if they are expanded and ui-corner-all if they are collapsed */
function clickNode(collapse, child)
{
if (collapse && child.classList.contains('ui-corner-top')) {
// console.log('collapse');
child.click();
}
if (!collapse && child.classList.contains('ui-corner-all')) {
// console.log('expand');
child.click();
}
}
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
##### Abstract [en]

##### Place, publisher, year, edition, pages

Umeå: Institutionen för matematik och matematisk statistik, Umeå universitet , 2011. , p. 30
##### Keywords [en]

stochastic processes, random fields, approximation, numerical integration, Hermite splines, piecewise linear interpolator, local stationarity, point singularity, stratified Monte Carlo quadrature, Asian option, Monte Carlo pricing method, Lévy market models
##### National Category

Probability Theory and Statistics
##### Research subject

Mathematical Statistics
##### Identifiers

URN: urn:nbn:se:umu:diva-46156ISBN: 978-91-7459-249-8 (print)OAI: oai:DiVA.org:umu-46156DiVA, id: diva2:437283
##### Public defence

2011-09-29, Samhällsvetarhuset, S213, Umeå Universitet, Umeå, 08:15 (English)
##### Opponent

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt455",{id:"formSmash:j_idt455",widgetVar:"widget_formSmash_j_idt455",multiple:true});
##### Supervisors

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt461",{id:"formSmash:j_idt461",widgetVar:"widget_formSmash_j_idt461",multiple:true});
#####

PrimeFaces.cw("AccordionPanel","widget_formSmash_j_idt467",{id:"formSmash:j_idt467",widgetVar:"widget_formSmash_j_idt467",multiple:true}); Available from: 2011-09-08 Created: 2011-08-26 Last updated: 2018-06-08Bibliographically approved
##### List of papers

In this thesis, we study numerical analysis for random processes and fields. We investigate the behavior of the approximation accuracy for specific linear methods based on a finite number of observations. Furthermore, we propose techniques for optimizing performance of the methods for particular classes of random functions. The thesis consists of an introductory survey of the subject and related theory and four papers (A-D).

In paper A, we study a Hermite spline approximation of quadratic mean continuous and differentiable random processes with an isolated point singularity. We consider a piecewise polynomial approximation combining two different Hermite interpolation splines for the interval adjacent to the singularity point and for the remaining part. For locally stationary random processes, sequences of sampling designs eliminating asymptotically the effect of the singularity are constructed.

In Paper B, we focus on approximation of quadratic mean continuous real-valued random fields by a multivariate piecewise linear interpolator based on a finite number of observations placed on a hyperrectangular grid. We extend the concept of local stationarity to random fields and for the fields from this class, we provide an exact asymptotics for the approximation accuracy. Some asymptotic optimization results are also provided.

In Paper C, we investigate numerical approximation of integrals (quadrature) of random functions over the unit hypercube. We study the asymptotics of a stratified Monte Carlo quadrature based on a finite number of randomly chosen observations in strata generated by a hyperrectangular grid. For the locally stationary random fields (introduced in Paper B), we derive exact asymptotic results together with some optimization methods. Moreover, for a certain class of random functions with an isolated singularity, we construct a sequence of designs eliminating the effect of the singularity.

In Paper D, we consider a Monte Carlo pricing method for arithmetic Asian options. An estimator is constructed using a piecewise constant approximation of an underlying asset price process. For a wide class of Lévy market models, we provide upper bounds for the discretization error and the variance of the estimator. We construct an algorithm for accurate simulations with controlled discretization and Monte Carlo errors, andobtain the estimates of the option price with a predetermined accuracy at a given confidence level. Additionally, for the Black-Scholes model, we optimize the performance of the estimator by using a suitable variance reduction technique.

1. Spline approximation of a random process with singularity$(function(){PrimeFaces.cw("OverlayPanel","overlay406794",{id:"formSmash:j_idt516:0:j_idt520",widgetVar:"overlay406794",target:"formSmash:j_idt516:0:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

2. Multivariate piecewise linear interpolation of a random field$(function(){PrimeFaces.cw("OverlayPanel","overlay565244",{id:"formSmash:j_idt516:1:j_idt520",widgetVar:"overlay565244",target:"formSmash:j_idt516:1:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

3. Stratified Monte Carlo quadrature for continuous random fields$(function(){PrimeFaces.cw("OverlayPanel","overlay565243",{id:"formSmash:j_idt516:2:j_idt520",widgetVar:"overlay565243",target:"formSmash:j_idt516:2:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

4. On the error of the Monte Carlo pricing method for Asian option$(function(){PrimeFaces.cw("OverlayPanel","overlay286810",{id:"formSmash:j_idt516:3:j_idt520",widgetVar:"overlay286810",target:"formSmash:j_idt516:3:partsLink",showEvent:"mousedown",hideEvent:"mousedown",showEffect:"blind",hideEffect:"fade",appendToBody:true});});

isbn
urn-nbn$(function(){PrimeFaces.cw("Tooltip","widget_formSmash_j_idt1177",{id:"formSmash:j_idt1177",widgetVar:"widget_formSmash_j_idt1177",showEffect:"fade",hideEffect:"fade",showDelay:500,hideDelay:300,target:"formSmash:altmetricDiv"});});

CiteExport$(function(){PrimeFaces.cw("TieredMenu","widget_formSmash_lower_j_idt1230",{id:"formSmash:lower:j_idt1230",widgetVar:"widget_formSmash_lower_j_idt1230",autoDisplay:true,overlay:true,my:"left top",at:"left bottom",trigger:"formSmash:lower:exportLink",triggerEvent:"click"});}); $(function(){PrimeFaces.cw("OverlayPanel","widget_formSmash_lower_j_idt1231_j_idt1233",{id:"formSmash:lower:j_idt1231:j_idt1233",widgetVar:"widget_formSmash_lower_j_idt1231_j_idt1233",target:"formSmash:lower:j_idt1231:permLink",showEffect:"blind",hideEffect:"fade",my:"right top",at:"right bottom",showCloseIcon:true});});