Add to ORKGThis bachelor thesis deals with the time series of binary variables that exist in many social spheres. The indicator may denote a certain value being exceeded or a phenomenon occurring. We study a model of logistic autoregression and its properties, partial likelihood function which allows us to work with dependent data, and derive useful relationships for a practical application that consists of time series simulation and real data analysis using free software R
This thesis deals with the detection of change in the structure of an autoregressive time series. In...
Some problems of' statistical inference for discrete-valued time series are investigated in this stu...
Markov chains and Mixture Transition Distribution are the most traditional models for binary time se...
This bachelor thesis deals with linear and nonlinear autoregressive models for time series from econ...
The problem of ergodicity, stationarity and maximum likelihood estimation is studied for binary time...
In the following thesis, we investigate the modeling of time series data with multivariate discrete ...
This bachelor thesis is primary focused on introducing models for categorical time series of nominal...
The classical autocorrelation function may not be an effective and informative means in revealing th...
This bachelor thesis deals with linear and bilinear models used for modelling time series data appli...
In the present bachelor thesis we study the selection of appropriate autoregression models to foreca...
Here we present a novel method for modeling stationary time series. Our approach is to construct the...
The bachelor thesis describes causality in multiple time series. Mul- tiple time series are formulat...
Bachelor thesis is focused on statistic methods for analysis and modelling time series. In particula...
The thesis deals with some of the non-linear Gaussian and non-Gaussian time models and mainly concen...
This thesis deals with analyzing multivariate financial and economical data. The first section descr...
This thesis deals with the detection of change in the structure of an autoregressive time series. In...
Some problems of' statistical inference for discrete-valued time series are investigated in this stu...
Markov chains and Mixture Transition Distribution are the most traditional models for binary time se...
This bachelor thesis deals with linear and nonlinear autoregressive models for time series from econ...
The problem of ergodicity, stationarity and maximum likelihood estimation is studied for binary time...
In the following thesis, we investigate the modeling of time series data with multivariate discrete ...
This bachelor thesis is primary focused on introducing models for categorical time series of nominal...
The classical autocorrelation function may not be an effective and informative means in revealing th...
This bachelor thesis deals with linear and bilinear models used for modelling time series data appli...
In the present bachelor thesis we study the selection of appropriate autoregression models to foreca...
Here we present a novel method for modeling stationary time series. Our approach is to construct the...
The bachelor thesis describes causality in multiple time series. Mul- tiple time series are formulat...
Bachelor thesis is focused on statistic methods for analysis and modelling time series. In particula...
The thesis deals with some of the non-linear Gaussian and non-Gaussian time models and mainly concen...
This thesis deals with analyzing multivariate financial and economical data. The first section descr...
This thesis deals with the detection of change in the structure of an autoregressive time series. In...
Some problems of' statistical inference for discrete-valued time series are investigated in this stu...
Markov chains and Mixture Transition Distribution are the most traditional models for binary time se...