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Visar resultat 1 - 5 av 51 avhandlingar som matchar ovanstående sökkriterier.
1. Goodness-of-fit in Multivariate Time Series
Sammanfattning : Goodness-of-fit is an important task in time series analysis. In this thesis, wepropose a new family of statistics and a new goodness-of-fit process for the wellknownmultivariate autoregressive moving average VARMA(p,q) model.Some preliminary results are studied first for an initial goodness-of-fit method. LÄS MER
2. On variance estimation and a goodness-of-fit test using the bootstrap method
Sammanfattning : This thesis deals with the study of variance estimation using the bootstrap method, including the problem of choosing between nonparametric and parametric bootstrap methods. Paper I compares the two approaches, determines which method is preferable and analyses the accuracy of the approximations. LÄS MER
3. On the Measurement of Model Fit for Sparse Categorical Data
Sammanfattning : This thesis consists of four papers that deal with several aspects of the measurement of model fit for categorical data. In all papers, special attention is paid to situations with sparse data. LÄS MER
4. Random Multigraphs : Complexity Measures, Probability Models and Statistical Inference
Sammanfattning : This thesis is concerned with multigraphs and their complexity which is defined and quantified by the distribution of edge multiplicities. Two random multigraph models are considered. The first model is random stub matching (RSM) where the edges are formed by randomly coupling pairs of stubs according to a fixed stub multiplicity sequence. LÄS MER
5. Maximum spacing methods and limit theorems for statistics based on spacings
Sammanfattning : The maximum spacing (MSP) method, introduced by Cheng and Amin (1983) and independently by Ranneby (1984), is a general estimation method for continuous univariate distributions. The MSP method, which is closely related to the maximum likelihood (ML) method, can be derived from an approximation based on simple spacings of the Kullback-Leibler information. LÄS MER