Home > Search Results: Kuželová, Noemi
Search:
Search Tips :: Advanced Search
Search collections:
Sort by: Display results: Output format:
National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Multivariate Cox point processes
 Kuželová, Noemi ; Dvořák, Jiří (advisor) ; Prokešová, Michaela (referee)
The Log-Gaussian Cox process is an important example of the use of spatial modeling and spatial statistics in practice. It is useful for describing many real-world situations, from modeling tree growth in the rainforests, to trying to understand the occurrence of precipitation and earthquakes, to examining the expansion of the Greenland seal pop- ulation. In this work we focus mainly on the multivariate form of this point process. Specially in such form that allows to describe at the same time inhomogeneity, clus- tering and environmental effects in the investigated system. When the parameters of multivariate LGCP process are estimated, the minimum contrast method is usually used. However, we investigate the possibility of using composite likelihood estimation instead. We consider the composite likelihood criterion as a limit of the likelihoods in approxi- mating discrete models. We compare it with an established approach of constructing the composite likelihood based on multiplication of likelihoods for pairs of points. 1
Detailed record
Variance stabilizing transformations
 Kuželová, Noemi ; Omelka, Marek (advisor) ; Komárek, Arnošt (referee)
Abstract. We often examine data whose sample mean converges to a normal distribution, but the variance generally depends on an unknown parameter. To get rid of this dependence, we can sometimes use the so-called variance-stabilizing transformation method. Firstly, this thesis explains the method in detail and finds a general procedure to find suitable transformations. Then it will focus on data from Poisson and binomial distributions with unknown parameters. For these data, it finds transformations that stabilize (asymptotic) variance, and compares them with the "improved"transforms from the article Anscombe (1948). Most of the thesis is devoted to the shape of these transformations. Finally, we show in the Poisson distribution simulation that it is really appropriate to use this method and compare the derived transformation with its Anscombe version.
Detailed record

See also: similar author names
1 Kuželová, Nikola
Interested in being notified about new results for this query?
Subscribe to the RSS feed.
Digital Repository :: Search :: Submit :: Personalize :: Help
Powered by Invenio v1.1.2
Maintained by admin.invenio@techlib.cz
This site is also available in the following languages:
Česky  English