Search for dissertations about: "goodness of fit"
Showing result 1 - 5 of 53 swedish dissertations containing the words goodness of fit.
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1. On the Measurement of Model Fit for Sparse Categorical Data
Abstract : 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. READ MORE
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2. Goodness-of-fit in Multivariate Time Series
Abstract : 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. READ MORE
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3. Some Contributions to Description and Validation of the Extreme Value Distribution
Abstract : This thesis focuses on the validation and description of the Gumbel distribution. Since this is a scale and location parameter distribution, the generalized least squares regression of the order statistics on the expected values can be used, without the necessity of iteration, to obtain the best linear unbiased estimates of the parameters. READ MORE
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4. On variance estimation and a goodness-of-fit test using the bootstrap method
Abstract : 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. READ MORE
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5. Modeling the covariance matrix of financial asset returns
Abstract : The covariance matrix of asset returns, which describes the fluctuation of asset prices, plays a crucial role in understanding and predicting financial markets and economic systems. In recent years, the concept of realized covariance measures has become a popular way to accurately estimate return covariance matrices using high-frequency data. READ MORE