calculate_lm_combo: Calculate a linear model for a linear combination of...
In jackmwolf/pcsstools: Tools for Regression Using Pre-Computed Summary Statistics

calculate_lm_combo

R Documentation

Calculate a linear model for a linear combination of responses

calculate_lm_combo describes the linear model for a linear combination of responses as a function of a set of predictors.

calculate_lm_combo(means, covs, n, phi, m = length(phi), add_intercept, ...)

`means`	a vector of means of all model predictors and the response with the last `m` elements the response means (with order corresponding to the order of weights in `phi`).
`covs`	a matrix of the covariance of all model predictors and the responses with the order of rows/columns corresponding to the order of `means`.
`n`	sample size.
`phi`	vector of linear combination weights with one entry per response variable.
`m`	number of responses to combine. Defaults to `length(weighs)`.
`add_intercept`	logical. If `TRUE` adds an intercept to the model.
`...`	additional arguments

an object of class "pcsslm".

An object of class "pcsslm" is a list containing at least the following components:

`call`	the matched call
`terms`	the `terms` object used
`coefficients`	a `p x 4` matrix with columns for the estimated coefficient, its standard error, t-statistic and corresponding (two-sided) p-value.
`sigma`	the square root of the estimated variance of the random error.
`df`	degrees of freedom, a 3-vector `p, n-p, p*`, the first being the number of non-aliased coefficients, the last being the total number of coefficients.
`fstatistic`	a 3-vector with the value of the F-statistic with its numerator and denominator degrees of freedom.
`r.squared`	`R^2`, the 'fraction of variance explained by the model'.
`adj.r.squared`	the above `R^2` statistic 'adjusted', penalizing for higher `p`.
`cov.unscaled`	a `p x p` matrix of (unscaled) covariances of the `coef[j], j=1,...p`.
`Sum Sq`	a 3-vector with the model's Sum of Squares Regression (SSR), Sum of Squares Error (SSE), and Sum of Squares Total (SST).