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The reciprocal transformation, some power transformations such as the Yeo–Johnson transformation, and certain other transformations such as applying the inverse hyperbolic sine, can be meaningfully applied to data that include both positive and negative values [10] (the power transformation is invertible over all real numbers if λ is an odd ...
These steps are often the focus of developers or technical data analysts who may use multiple specialized tools to perform their tasks. The steps can be described as follows: Data discovery is the first step in the data transformation process. Typically the data is profiled using profiling tools or sometimes using manually written profiling ...
Pages in category "Statistical data transformation" The following 11 pages are in this category, out of 11 total. This list may not reflect recent changes. ...
In statistics, completeness is a property of a statistic computed on a sample dataset in relation to a parametric model of the dataset. It is opposed to the concept of an ancillary statistic . While an ancillary statistic contains no information about the model parameters, a complete statistic contains only information about the parameters, and ...
The transformation suggested by Cochrane and Orcutt disregards the first observation of a time series, causing a loss of efficiency that can be substantial in small samples. [3] A superior transformation, which retains the first observation with a weight of ( 1 − ρ 2 ) {\displaystyle {\sqrt {(1-\rho ^{2})}}} was first suggested by Prais and ...
In statistics, a power transform is a family of functions applied to create a monotonic transformation of data using power functions.It is a data transformation technique used to stabilize variance, make the data more normal distribution-like, improve the validity of measures of association (such as the Pearson correlation between variables), and for other data stabilization procedures.
The transformation is called "whitening" because it changes the input vector into a white noise vector. Several other transformations are closely related to whitening: the decorrelation transform removes only the correlations but leaves variances intact, the standardization transform sets variances to 1 but leaves correlations intact,
In statistics, sufficiency is a property of a statistic computed on a sample dataset in relation to a parametric model of the dataset. A sufficient statistic contains all of the information that the dataset provides about the model parameters.