Similar Search Results

Multiple Regression with Integrated Time Series

Phillips, Peter C.B. - Cowles Foundation for Research in Economics, Yale University - 1987

Recent work on the theory of regression with integrated process is reviewed. This work is particularly relevant in economics where many financial series and macroeconomic time series exhibit nonstationary characteristics and are often well modeled individually as simple ARIMA processes. The...

Persistent link: https://www.econbiz.de/10005762610

Role of Dependence in Chance-constrained and Robust Programming

Houda, Michal - In: Acta Oeconomica Pragensia 2007 (2007) 4, pp. 111-120

The paper deals with two methods of solving optimization programs where uncertainties occur: stochastic (in particular chance-constrained) programming and robust programming. We review briefly how these two methods deal with uncertainty and what approximations are commonly used. Furthermore, we...

Persistent link: https://www.econbiz.de/10005036303

Sieve Inference on Semi-nonparametric Time Series Models

Chen, Xiaohong; Liao, Zhipeng; Sun, Yixiao - Cowles Foundation for Research in Economics, Yale University - 2012

indicate that our scaled "pre-asymptotic" Wald test with F critical values has more accurate size in finite samples than the … usual Wald test with chi-square critical values. …

Persistent link: https://www.econbiz.de/10009649696

Asymptotic theory for nonparametric regression with spatial data

Robinson, P.M. - In: Journal of Econometrics 165 (2011) 1, pp. 5-19

Nonparametric regression with spatial, or spatio-temporal, data is considered. The conditional mean of a dependent variable, given explanatory ones, is a nonparametric function, while the conditional covariance reflects spatial correlation. Conditional heteroscedasticity is also allowed, as well...

Persistent link: https://www.econbiz.de/10010574099

Asymptotic distribution of two-sample empirical U-quantiles with applications to robust tests for shifts in location

Dehling, Herold; Fried, Roland - In: Journal of Multivariate Analysis 105 (2012) 1, pp. 124-140

theoretical results we propose a new robust nonparametric test for the two-sample location problem, which is constructed from the … median of pairwise differences between the two samples. We inspect the properties of the test in the case of weakly dependent … data and compare the performance with classical tests such as the t-test and Wilcoxon’s two-sample rank test with …

Persistent link: https://www.econbiz.de/10010576501

Valid Locally Uniform Edgeworth Expansions Under Weak Dependence and Sequences of Smooth Transformations

Demos, Antonis; Arvanitis, Stelios - Department of International and European Economic … - 2012

In this paper we are concerned with the issue of the existence of locally uniform Edgeworth expansions for the distributions of random vectors. Our motivation resides on the fact that this could enable subsequent uniform approximations of analogous moments and their derivatives. We derive...

Persistent link: https://www.econbiz.de/10010551764

Sample Covariance Shrinkage for High Dimensional Dependent Data

Sancetta, A. - Faculty of Economics, University of Cambridge - 2006

For high dimensional data sets the sample covariance matrix is usually unbiased but noisy if the sample is not large enough. Shrinking the sample covariance towards a constrained, low dimensional estimator can be used to mitigate the sample variability. By doing so, we introduce bias, but reduce...

Persistent link: https://www.econbiz.de/10005650534

Inference on the Limiting False Discovery Rate and the P-value Threshold Parameter Assuming Weak Dependence between Gene Expression Levels within Subject

Heller, Glenn; Qin, Jing - In: Statistical Applications in Genetics and Molecular Biology 6 (2007) 1, pp. 14-14

outcome. For each gene, a test statistic is computed to determine if an association exists, and this statistic generates a … normality of the test statistic. The p-values are assumed to be weakly dependent and a quasi-likelihood is used to estimate the …

Persistent link: https://www.econbiz.de/10005585087

Limit Theory for Moderate Deviations from a Unit Root under Weak Dependence

Phillips, Peter C.B.; Magadalinos, Tassos - Cowles Foundation for Research in Economics, Yale University - 2005

An asymptotic theory is given for autoregressive time series with weakly dependent innovations and a root of the form rho_{n} = 1+c/n^{alpha}, involving moderate deviations from unity when alpha in (0,1) and c in R are constant parameters. The limit theory combines a functional law to a...

Persistent link: https://www.econbiz.de/10005593308

Efficient Regression in Time Series Partial Linear Models

Phillips, Peter C.B.; Guo, Binbin; Xiao, Zhijie - Cowles Foundation for Research in Economics, Yale University - 2002

This paper studies efficient estimation of partial linear regression in time series models. In particular, it combines two topics that have attracted a good deal of attention in econometrics, viz. spectral regression and partial linear regression, and proposes an efficient frequency domain...

Persistent link: https://www.econbiz.de/10005593565