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Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered, tends to increase or decrease over time, or is influenced by changes in an external factor. Linear trend estimation essentially creates a straight line on a graph of data that models the general ...
Jonckheere's trend test. In statistics, the Jonckheere trend test[ 1] (sometimes called the Jonckheere–Terpstra[ 2] test) is a test for an ordered alternative hypothesis within an independent samples (between-participants) design. It is similar to the Kruskal-Wallis test in that the null hypothesis is that several independent samples are from ...
Structural break. In econometrics and statistics, a structural break is an unexpected change over time in the parameters of regression models, which can lead to huge forecasting errors and unreliability of the model in general. [ 1][ 2][ 3] This issue was popularised by David Hendry, who argued that lack of stability of coefficients frequently ...
In statistics, best linear unbiased prediction ( BLUP) is used in linear mixed models for the estimation of random effects. BLUP was derived by Charles Roy Henderson in 1950 but the term "best linear unbiased predictor" (or "prediction") seems not to have been used until 1962. [ 1] ". Best linear unbiased predictions" (BLUPs) of random effects ...
e. In statistics, linear regression is a statistical model which estimates the linear relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables ). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear ...
e. Segmented regression, also known as piecewise regression or broken-stick regression, is a method in regression analysis in which the independent variable is partitioned into intervals and a separate line segment is fit to each interval. Segmented regression analysis can also be performed on multivariate data by partitioning the various ...
The Cochran–Armitage test for trend, [1] [2] named for William Cochran and Peter Armitage, is used in categorical data analysis when the aim is to assess for the presence of an association between a variable with two categories and an ordinal variable with k categories. It modifies the Pearson chi-squared test to incorporate a suspected ...
These two trends construct a reverse u-shape relationship between model complexity and R 2, which is in consistent with the u-shape trend of model complexity vs. overall performance. Unlike R 2 , which will always increase when model complexity increases, R 2 will increase only when the bias eliminated by the added regressor is greater than the ...