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Fitting autoregressive models for prediction
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This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models in a stationary time series.Abstract:
This is a preliminary report on a newly developed simple and practical procedure of statistical identification of predictors by using autoregressive models. The use of autoregressive representation of a stationary time series (or the innovations approach) in the analysis of time series has recently been attracting attentions of many research workers and it is expected that this time domain approach will give answers to many problems, such as the identification of noisy feedback systems, which could not be solved by the direct application of frequency domain approach [1], [2], [3], [9].read more
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The choice of a genetic model in the meta-analysis of molecular association studies
TL;DR: A genetic model-free approach is presented, which does not assume that the underlying genetic model is known in advance but still makes use of the information available on all genotypes, and offers a unified approach that efficiently estimates the genetic effect and the underlying Genetic model.
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Electricity generation and economic growth in Indonesia
Seung-Hoon Yoo,Yeonbae Kim +1 more
TL;DR: In this article, the authors investigated the causal relationship between electricity generation and economic growth in Indonesia, using time-series techniques for the period of 1971-2002 and found that there is a uni-directional causality running from economic growth to electricity generation without any feedback effect.
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Incorporating Landscape Attributes into Models for Migratory Grassland Bird Conservation
TL;DR: The authors evaluated the influence of local and landscape attributes on the occurrence and density of seven passerine species in grasslands (n � 380) throughout eastern South Dakota (U.S.A.).
The New Palgrave Dictionary of Economics Online
TL;DR: The economic approach to valuing risks to life focuses on risk-money trade-offs for very small risks of death, or the value of statistical life (VSL), which will generally exceed the optimal insurance amounts.
Journal ArticleDOI
Neural networks and logistic regression: Part I
TL;DR: A comparative investigation of both logistic regression models and feed-forward neural networks including some extensions is presented and the theoretical features and properties are reviewed and illustrated in two examples.
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