安裝中文字典英文字典辭典工具!
安裝中文字典英文字典辭典工具!
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- Why are regression problems called regression problems?
Origin of 'regression' The term "regression" was coined by Francis Galton in the 19th century to describe a biological phenomenon The phenomenon was that the heights of descendants of tall ancestors tend to regress down towards a normal average (a phenomenon also known as regression toward the mean)(Galton, reprinted 1989)
- correlation - What is the difference between linear regression on y . . .
The insight that since Pearson's correlation is the same whether we do a regression of x against y, or y against x is a good one, we should get the same linear regression is a good one It is only slightly incorrect, and we can use it to understand what is actually occurring
- regression - What does it mean to regress a variable against another . . .
As an example, the data is X = 1, ,100 The value of Y is plotted on the Y axis The red line is the linear regression surface Personally, I don't find the independent dependent variable language to be that helpful Those words connote causality, but regression can work the other way round too (use Y to predict X)
- regression - Trying to understand the fitted vs residual plot? - Cross . . .
In this example, variances for the first quarter of the data, up to about a fitted value of 40 are smaller than variances for fitted values larger than 40 The middle portion of the fitted values has substantially larger variances than the outer values This indicates that the regression model may have failed to account for heteroscedasticity
- regression - What is the correct formula to compute R-squared? - Cross . . .
I'm completely confused about how to calculate R-squared for given lists of predicted and actual values As an example, assume that my predicted values are: [3, 8, 10, 17, 24, 27] and my actual va
- regression - Is it optimal to run 18 LMMs with Bonferroni correction . . .
One example, and probably the most straightforward, is to construct a system of simultaneously estimated regression paths using maximum likelihood, in what we would normally call path analysis The actual estimation on the user's end is rather simple: simply estimate the regression paths you want But you can add as many relationships as you
- regression - How to Perform Cross-Validation for LASSO in GAMLSS to . . .
I am working with a Generalized Additive Model for Location, Scale, and Shape (GAMLSS) and trying to determine the optimal $\lambda$ values for LASSO-penalized regression using cross-validation However, I am struggling to understand how to properly set up the cross-validation procedure in this context
- regression - Why do we say the outcome variable is regressed on the . . .
The word "regressed" is used instead of "dependent" because we want to emphasise that we are using a regression technique to represent this dependency between x and y So, this sentence "y is regressed on x" is the short format of: Every predicted y shall "be dependent on" a value of x through a regression technique
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