lm_coefs: Linear Model Coefficients
In kazaam: Tools for Tall Distributed Matrices

Description Usage Arguments Details Value Communication See Also Examples

Coefficients of the linear model.

1	lm_coefs(x, y, tol = 1e-07)

`x, y`	The input data `x` and response `y`. Each must be a shaq, and each must be distributed in an identical fashion. See the details section for more information.
`tol`	Numerical tolerance for deciding rank.

The model is fit using a QR factorization of the input x. At this time, that means

Both of x and y must be distributed in an identical fashion. This means that the number of rows owned by each MPI rank should match, and the data rows x and labels y should be aligned. Additionally, each MPI rank should own at least one row. Ideally they should be load balanced, so that each MPI rank owns roughly the same amount of data.

A regular vector.

The operation has the same communication as

glms

## Not run: 
library(kazaam)
comm.set.seed(1234, diff=TRUE)

x = ranshaq(rnorm, 10, 3)
y = ranshaq(runif, 10)

fit = lm_coefs(x, y)
comm.print(fit)

finalize()

## End(Not run)