• Publications
  • Influence
Time Series Analysis by State Space Methods
  • M. Hinich
  • Mathematics, Computer Science
  • Technometrics
  • 1 August 2005
TLDR
Overall, Linear Models With R is well written and, given the increasing popularity of R, it is an important contribution. Expand
Testing for Gaussianity and Linearity of a Stationary Time Series.
Abstract. Stable autoregressive (AR) and autoregressive moving average (ARMA) processes belong to the class of stationary linear time series. A linear time series {} is Gaussian if the distributionExpand
The Spatial Theory of Voting: An Introduction
Preface 1. Spatial voting models: the behavioural assumptions 2. The unidimensional spatial voting model 3. A two-dimensional spatial model 4. A general spatial model of candidate competition 5. TheExpand
A Single-Blind Controlled Competition among Tests for Nonlinearity and Chaos
This is the FINAL draft of this paper reporting the results of a long ongoing competition. The paper now is forthcoming in the Journal of Econometrics. This final version replaces the earlier draftExpand
Testing for dependence in the input to a linear time series model
This paper presents a simple test for dependence in the residuals of a linear parametric time series model fitted to non gaussian data. The test statistic is a third order extension of the standardExpand
Ideology and the theory of political choice
There is no unified theory that can explain both voter choice and where choices come from. Hinich and Munger fill that gap with their model of political communication based on ideology.Rather thanExpand
The Spatial Theory Of Voting
This book provides an introduction to an important approach to the study of voting and elections: the spatial theory of voting. In contrast to the social-psychological approach to studying votingExpand
Evidence of Nonlinearity in Daily Stock Returns
This article applies a newly developed statistical technique to time series of daily rates of return of 15 common stocks. The technique involves estimating the bispectrum of the observed time series.Expand
Time series test of nonlinear convergence and transitional dynamics
This paper revisits the income convergence hypothesis by using the nonlinear unit root test of Kapetanios et al. [Kapetanios, G., Shin, Y. and A. Snell, 2003. Testing for a unit root in the nonlinearExpand
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