Finite sample properties of nonstationary binary response models: A monte carlo analysis

2003 ◽  
Vol 73 (3) ◽  
pp. 203-222 ◽  
Author(s):  
Mary Riddel
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Analysis ◽  
Binary Response ◽  
Finite Sample ◽  
Response Models ◽  
Finite Sample Properties ◽  
Binary Response Models

scholarly journals Maximum Non-Extensive Entropy Block Bootstrap for Non-stationary Processes

2016 ◽  
Vol 91 (1-2) ◽  
pp. 115-139 ◽  
Author(s):  
Michele Bergamelli ◽  
Jan Novotný ◽  
Giovanni Urga
Keyword(s):  
Time Series ◽  
Monte Carlo ◽  
Maximum Entropy ◽  
Rank Correlation ◽  
Monte Carlo Analysis ◽  
Stationary Processes ◽  
Block Bootstrap ◽  
Finite Sample ◽  
Tail Behaviour ◽  
Finite Sample Properties

In this paper, we propose a novel entropy-based resampling scheme valid for non-stationary data. In particular, we identify the reason for the failure of the original entropy-based algorithm of Vinod and López-de Lacalle (2009) to be the perfect rank correlation between the actual and bootstrapped time series. We propose the Maximum Entropy Block Bootstrap which preserves the rank correlation locally. Further, we also introduce the Maximum non-extensive Entropy Block Bootstrap to allow for fat tail behaviour in time series. Finally, we show the optimal finite sample properties of the proposed methods via a Monte Carlo analysis where we bootstrap the distribution of the Dickey-Fuller test.

scholarly journals Binary response models withM-phase case-control data

2013 ◽  
Vol 116 ◽  
pp. 332-348
Author(s):  
Chin-Tsang Chiang ◽  
Ming-Yueh Huang ◽  
Ren-Hong Bai
Keyword(s):  
Case Control ◽  
Binary Response ◽  
Control Data ◽  
Response Models ◽  
Binary Response Models
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