Results 101 to 110 of about 13,095 (150)

How Robust is Robust Control in the Time Domain? [PDF]

By applying robust control the decision maker wants to make good decisions when his model is only a good approximation of the true one. Such decisions are said to be robust to model misspecification.
Marco P. Tucci
core  

Agent‐based versus correlative models of species distributions: Evaluation of predictive performance with real and simulated data

Methods in Ecology and Evolution
Species distribution models (SDMs) have been widely used in ecology to understand how species relate to environmental variation. Most SDMs are correlative, and they lack explicit reference to the underlying processes, and therefore, the reliability of ...
Jukka Sirén, Panu Somervuo, Otso Ovaskainen   +2 more
doaj   +1 more source

Panel AR(1) estimators under misspecification

This short note derives the probability limits of several estimators for panel AR(1) models under misspecification using sequential asymptotics. The results show that GMM estimators based on the forward orthogonal deviation transformation converge to the
Okui, Ryo
core  

Revisiting Simpson's Paradox: a statistical misspecification perspective

, 2016
The primary objective of this paper is to revisit Simpson's paradox using a statistical misspecification perspective. It is argued that the reversal of statistical associations is sometimes spurious, stemming from invalid probabilistic assumptions ...
Spanos, Aris
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Robust Design and Misspecification Detection for Count Models

Count models, such as the Poisson and negative binomial models, are widely utilized in various fields, including epidemiology, engineering, and social sciences, to model the occurrence of events within fixed periods of time or space.
Slessor, Jordan
core   +1 more source

Exchange Rate Expectations and Functional Misspecification.

The authors employ the Cooley-Prescott adaptive model to examine for functional misspecification in three commonly used exchange rate expectation models. They also test for heterogeneity among forecasts.
Boyd, Roy, Doroodian, Khosrow
core  

Robustness to model misspecification in Bayesian experimental design

Scientific experiments can be costly to conduct due to various reasons. Therefore, researchers need to choose the experimental design which allows them to obtain the highest amount of information possible. As an information-theoretical framework based on
Ulukir, Behram
core   +1 more source

Model Misspecification and Underdiversification

The Journal of Finance, 2001
AbstractIn this paper, we study intertemporal portfolio choice when an investor accounts explicitly for model misspecification. We develop a framework that allows for ambiguity about not just the joint distribution of returns for all stocks in the portfolio, but also for different levels of ambiguity for the marginal distribution of returns for any ...
Uppal, Raman, Wang, Tan
core   +4 more sources

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The Misspecification of Arma Models

Statistica Neerlandica, 1989
The object of this paper is to assess the effects of fitting a model of the wrong order to a time series which is generated by an autoregressive moving–average process. The method is to examine the spectral density functions which are indicated by the probability limits of the least–squares estimators of the misspecified models.
openaire   +2 more sources

The Effects of Misspecification of a Regression Model

Biometrical Journal, 1987
AbstractThe consequences of the misspecification of a regression model are considered. For small effects of covariates a proportional consistency theorem is derived. The consistent estimation of the covariance matrix of the estimates is discussed.
Nagelkerke, N. J. D., Hart, A. A. M., Oosting, J.   +2 more
openaire   +1 more source