# Questions tagged [r-squared]

The coefficient of determination, usually symbolized by $R^2$, is the proportion of the total response variance explained by a regression model. Can also be used for various pseudo R-squared proposed, for instance for logistic regression (and other models.)

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### Calculating pseudo-$R^2$ for out-of-sample probit model forecasts

I'm trying to replicate parts of: Estrella, A., & Mishkin, F. S. (1998). Predicting U.S. Recessions: Financial Variables as Leading Indicators. Review of Economics and Statistics, 80(1), 45–61. ...
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### Averaging R2 between different sized test sets

I'm testing a model using different tests sets. In fact, I'm mimicking cross validation but since my data is correlated I used data from individual years as test sets instead of assigning my data ...
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### Computing $\text{pseudo} ~R^2$ and $R^2_{adj}$ of a cforest model

I would like to know how we can retrieve (or compute) $R^2$ when the function cforest() from the package party is used. The ...
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### Is it possible to calculate a pseudo-R squared for a binomial GLMM with a cauchit link?

I'm modeling some repeated-measures presence-absence data using a binomial GLMM in lme4. I've been using the method suggested by Nakagawa and Schielzeth (2013) to calculate a marginal and conditional ...
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### Relation between bias and R-square

I am trying to understand relation between bias and R-squared value in linear regression. High bias means that the model is underfit. By this I am assuming that the R-square d will be less. So my ...
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### Coefficient of determination in time series models

Nagelkerke's (1991) generalized $R^{2}$ (below) is a modification of the Cox Snell (1989) generalized $R^{2}$ (the numerator in the below) which is a coefficient of determination based on the log-...
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### How to compare transformed and untransformed linear models?

I have a linear model which doesn't have any particular issues with its assumptions (diagnostics plots look well). However it has a slighly skewed response (skewness approx. 0.5) and few skew ...
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### Interpretation of R-squared when using FGLS

Context: I am analyzing time series and cross-sectional data using Stata's xtpcse command which corrects for autocorrelation in panel data using a Prais–Winsten ...
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### Help explain the "redundancy" of canonical correlation

I am reading a material about canonical correlation and it introduces a concept named "redundancy". I have been puzzled for one day but still could not get a understanding. The following is a screen ...
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### Weighted Adjusted R2

I understand the r2 metric, being 1- (rss /tss) where rss = sum of squared residuals and tss = total sum of squares I understand how to weight this, such as when each row is a population, and some ...
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