This paper presents a classification of statistical models using a simple and logical framework. Some remarks are made about the historical appearance of each type of model and the practical problems that motivated them. It is argued that the current stages of the statistical methodology for model building have arisen in response to the needs for more sophisticated procedures for building dynamic-explicative types of models. Some potentially important topics for future research are include
According to a standard point of view, statistical modelling consists in establishing a parsimonious...
The features of a logically sound approach to a theory of statistical reasoning are discussed. A par...
Key Vords and Phrases- model formula~~on and selec~~on; plann~ng ~nves~~ga~ions; ra~ios of random va...
R. A. Fisher founded modern statistical inference in 1922 and identified its fundamental problems to...
Statistical thinking has gained importance recently. The purpose of the research study is to analyze...
この論文は国立情報学研究所の電子図書館事業により電子化されました。There are a number of statistical methodologies, each of which has ...
We describe statistical modeling as a powerful alternative to null hypothesis significance testing (...
Lenhard J. Models and statistical inference: The controversy between Fisher and Neyman-Pearson. Brit...
The problem of statistical model selection in econometrics and statistics is reviewed. Model selecti...
This volume contains a collection of papers which were presented at the fourth Franco-Belgian Meetin...
We describe a new language for statistical data modeling. The language offers a general framework fo...
This textbook on statistical modeling and statistical inference will assist advanced undergraduate a...
In the situations typically encountered in the social sciences the methodology of traditional statis...
We point out that models based on probability theory, and the statistical techniques derived from t...
Often scientific information on various data generating processes are presented in the from of numer...
According to a standard point of view, statistical modelling consists in establishing a parsimonious...
The features of a logically sound approach to a theory of statistical reasoning are discussed. A par...
Key Vords and Phrases- model formula~~on and selec~~on; plann~ng ~nves~~ga~ions; ra~ios of random va...
R. A. Fisher founded modern statistical inference in 1922 and identified its fundamental problems to...
Statistical thinking has gained importance recently. The purpose of the research study is to analyze...
この論文は国立情報学研究所の電子図書館事業により電子化されました。There are a number of statistical methodologies, each of which has ...
We describe statistical modeling as a powerful alternative to null hypothesis significance testing (...
Lenhard J. Models and statistical inference: The controversy between Fisher and Neyman-Pearson. Brit...
The problem of statistical model selection in econometrics and statistics is reviewed. Model selecti...
This volume contains a collection of papers which were presented at the fourth Franco-Belgian Meetin...
We describe a new language for statistical data modeling. The language offers a general framework fo...
This textbook on statistical modeling and statistical inference will assist advanced undergraduate a...
In the situations typically encountered in the social sciences the methodology of traditional statis...
We point out that models based on probability theory, and the statistical techniques derived from t...
Often scientific information on various data generating processes are presented in the from of numer...
According to a standard point of view, statistical modelling consists in establishing a parsimonious...
The features of a logically sound approach to a theory of statistical reasoning are discussed. A par...
Key Vords and Phrases- model formula~~on and selec~~on; plann~ng ~nves~~ga~ions; ra~ios of random va...