Description Usage Arguments Details Value Author(s) Examples
Fast computation of simple regression slopes for each predictor represented by a column in a matrix
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y |
A vector of outcomes. |
X |
A design matrix of regressor variables. Must have the same number of rows as the length of y. |
weight |
A vector of weights for each observation that are used in the estimation. |
maxit |
the maximum number of iterations to use for the EM algorithm |
tol |
the tolerance used for determining convergence |
alpha |
the starting probability for an observation originating from the contamination distribution. Must be strictly between 0 and 1 |
mu |
the starting value for the mean of the contamination distribution. If set to NA (the default) then the mean of the y vector is used. |
mufixed |
Should the value ... |
Missing values (NA, Inf, NaN) are completely disregarded and pairwise complete cases are used for the analysis.
A list with the variables: N, K, coefficients, mu, sigma1, sigma2, alpha, iterationsused, and groupprob which contains information on the nuber of observations, mixture components, coefficients for ...
Claus Ekstrom <ekstrom@sund.ku.dk>
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