Journal ArticleDOI
An Analysis of Transformations
George E. P. Box,David Cox +1 more
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In this article, Lindley et al. make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's.Abstract:
[Read at a RESEARCH METHODS MEETING of the SOCIETY, April 8th, 1964, Professor D. V. LINDLEY in the Chair] SUMMARY In the analysis of data it is often assumed that observations Yl, Y2, *-, Yn are independently normally distributed with constant variance and with expectations specified by a model linear in a set of parameters 0. In this paper we make the less restrictive assumption that such a normal, homoscedastic, linear model is appropriate after some suitable transformation has been applied to the y's. Inferences about the transformation and about the parameters of the linear model are made by computing the likelihood function and the relevant posterior distribution. The contributions of normality, homoscedasticity and additivity to the transformation are separated. The relation of the present methods to earlier procedures for finding transformations is discussed. The methods are illustrated with examples.read more
Citations
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On the use of structural equation models in experimental designs
Richard P. Bagozzi,Youjae Yi +1 more
TL;DR: The authors begin with one-way designs, including overall tests of significance, step-down analyses, and the use of latent variables, and describe a general test of homogeneity and consider a procedure that is applicable even under conditions of heterogeneity.
Journal ArticleDOI
Characteristic-Based Clustering for Time Series Data
TL;DR: This paper proposes a method for clustering of time series based on their structural characteristics, which reduces the dimensionality of the time series and is much less sensitive to missing or noisy data.
Journal ArticleDOI
Robust statistical methods in R using the WRS2 package.
Patrick Mair,Rand R. Wilcox +1 more
TL;DR: The R package WRS2 is introduced that implements various robust statistical methods by introducing robust location, dispersion, and correlation measures, and robust ANCOVA as well as robust mediation models are introduced.
Journal ArticleDOI
Do not log-transform count data
Robert B. O'Hara,D. Johan Kotze +1 more
TL;DR: This work compared the outcome of fitting models that were transformed in various ways with results from fitting models using Poisson and negative binomial models to untransformed count data, finding that the transformations performed poorly, except when the dispersion was small and the mean counts were large.
Journal ArticleDOI
The Use of Artificial Neural Networks for the Prediction of Water Quality Parameters
Holger R. Maier,Graeme C. Dandy +1 more
TL;DR: In this article, a case study is presented in which ANN methods are used to forecast salinity in the River Murray at Murray Bridge (South Australia) 14 days in advance, and the results obtained were most promising.
References
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Book
Theory of probability
Harold Jeffreys,R. Bruce Lindsay +1 more
TL;DR: In this paper, the authors introduce the concept of direct probabilities, approximate methods and simplifications, and significant importance tests for various complications, including one new parameter, and various complications for frequency definitions and direct methods.
Journal ArticleDOI
Theory of Probability.
Ernest Nagel,Harold Jeffreys +1 more
TL;DR: In this paper, the authors introduce the concept of direct probabilities, approximate methods and simplifications, and significant importance tests for various complications, including one new parameter, and various complications for frequency definitions and direct methods.
Book ChapterDOI
Properties of Sufficiency and Statistical Tests
TL;DR: In this article, the structure of small sample tests, whether these are related to problems of estimation and fiducial distributions, or are of the nature of tests of goodness of fit, is considered further.
Journal ArticleDOI
The use of transformations.
TL;DR: In this paper, the authors summarize the transformations which have been used on raw statistical data, with particular reference to analysis of variance, and the usual purpose of the transformation is to change the scale of the measurements in order to make the analysis more valid.
Journal ArticleDOI
One Degree of Freedom for Non-Additivity
TL;DR: The present writer is usually much more concerned with and worried about non-additivity, and until recently has suffered from the lack of a systematic way to seek it out, and then to measure it.