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# Download Testing for Random Walk Coefficients in Regression and State Space Models (Contributions to Statistics) eBook

## by Martin Moryson ISBN:
3790811327
Author:
Martin Moryson
Category:
Mathematics
Language:
English
Publisher:
Physica (April 15, 1999)
Pages:
317 pages
EPUB book:
1947 kb
FB2 book:
1525 kb
DJVU:
1315 kb
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Rating:
4.7
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Regression and state space models with time varying coefficients are treated in a thorough manner. Exact Tests for Univariate Random Walk Coefficients.

Regression and state space models with time varying coefficients are treated in a thorough manner. State space models are introduced as a means to model time varying regression coefficients. Asymptotic Tests for Univariate Random Walk Coefficients in Models with Stationary Regressors.

Introduction Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time.

Exact Tests for Univariate Random Walk Coefficients. This chapter deals with testing for univariate random walk coefficients in regression models in which non-stationary regressors are present. In the previous chapter the linear state space model was discussed and some estimation methods were proposed. As stated in the previous chapter, the distributions of the test statistics change if non-stationary regressors are included. First, integrated regressors are considered, . either x1,t or x2,t will contain I(1) regressors.

Contributions to statistics

Contributions to statistics. On this site it is impossible to download the book, read the book online or get the contents of a book. The administration of the site is not responsible for the content of the site. The data of catalog based on open source database. All rights are reserved by their owners. Download book Testing for random walk coefficients in regression and state space models, Martin Moryson.

State space models are introduced as a means to model time varying regression coefficients. The main part of the book deals with testing the null hypothesis of constant regression coefficients against the alternative that they follow a random walk. Different exact and large sample tests are presented and extensively compared based on Monte Carlo studies, so that the reader is guided in the question which test to choose in a particular situation.

Testing a null variance ratio in mixed models with zero degrees of freedom . arley, . A test for a shifting slope coefficient in a linear model

Testing a null variance ratio in mixed models with zero degrees of freedom for error. Computational Statistics & Data Analysis, Vol. 46, Issue. The locally best invariant statistic to test for the constancy of regression coefficients under a random walk alternative is shown to be the same as a Bayesian-type statistic derived under a change-point alternative. Asymptotic theory for this and more general statistics is discussed. Export citation Request permission. A test for a shifting slope coefficient in a linear model. Journal of the American Statistical Association 65 (1970): 1320–1329. State space models are introduced as a means to model time varying regression coefficients

Regression and state space models with time varying coefficients are treated in a thorough manner.

In the simple case where we want to test whether some parameters are zero, the R matrix has a 1 in the column corresponding to the position of the parameter and zeros everywhere else, and q is zero, which is the default. Each row specifies a linear combination of parameters, which defines a hypothesis as part of the overall or joint hypothesis

Statistics is the discipline that concerns the collection, organization, displaying, analysis, interpretation and presentation of data.

Statistics is the discipline that concerns the collection, organization, displaying, analysis, interpretation and presentation of data. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal"

Regression and state space models with time varying coefficients are treated in a thorough manner. State space models are introduced as a means to model time varying regression coefficients. The Kalman filter and smoother recursions are explained in an easy to understand fashion. The main part of the book deals with testing the null hypothesis of constant regression coefficients against the alternative that they follow a random walk. Different exact and large sample tests are presented and extensively compared based on Monte Carlo studies, so that the reader is guided in the question which test to choose in a particular situation. Moreover, different new tests are proposed which are suitable in situations with autocorrelated or heteroskedastic errors. Additionally, methods are developed to test for the constancy of regression coefficients in situations where one knows already that some coefficients follow a random walk, thereby one is enabled to find out which of the coefficients varies over time.

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