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2021
Frequentist probability is historically presented as an attempt both to overcome the limitations of classical conception and to take into account the impressive development of experimental sciences and statistics. It is precisely because of this close link with the statistical sciences that it finds a significant place in teaching.
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Frequentist probability is historically presented as an attempt both to overcome the limitations of classical conception and to take into account the impressive development of experimental sciences and statistics. It is precisely because of this close link with the statistical sciences that it finds a significant place in teaching.
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Bayesian Versus Frequentist Inference
2008Throughout this book, the topic of order restricted inference is dealt with almost exclusively from a Bayesian perspective. Some readers may wonder why the other main school for statistical inference – frequentist inference – has received so little attention here.
Wagenmakers, E.-J. +3 more
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2019
This chapter summarises the recent approaches to optimal forecast combination from a frequentist perspective. The availability of big data leads to the development of many different models of the same macroeconomic variables. The challenge is to seek the best way to combine all relevant information from big data to create optimal forecast.
Chan, Felix, Pauwels, L., Soltyk, S.
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This chapter summarises the recent approaches to optimal forecast combination from a frequentist perspective. The availability of big data leads to the development of many different models of the same macroeconomic variables. The challenge is to seek the best way to combine all relevant information from big data to create optimal forecast.
Chan, Felix, Pauwels, L., Soltyk, S.
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2023
Abstract This chapter focuses on the frequentist approach to “saying something about” the model parameters—specifically, how to estimate their values and why some ways of estimating them may be better than others. Topics include: maximum likelihood; mean squared error; Newton’s method; EM algorithm.
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Abstract This chapter focuses on the frequentist approach to “saying something about” the model parameters—specifically, how to estimate their values and why some ways of estimating them may be better than others. Topics include: maximum likelihood; mean squared error; Newton’s method; EM algorithm.
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2001
Abstract Frequentist or repeated sampling properties of sample statistics form a basis of probability-based inference. These properties also indicate a potential objective verification of our statistical procedures. In this chapter we will expand our discussion on important frequentist properties such as bias and variance of point ...
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Abstract Frequentist or repeated sampling properties of sample statistics form a basis of probability-based inference. These properties also indicate a potential objective verification of our statistical procedures. In this chapter we will expand our discussion on important frequentist properties such as bias and variance of point ...
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Frequentist Probability Theory
2008info:eu-repo/semantics ...
Hörmann, Siegfried, Friedl, H.
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