Published
Edited
Nov 11, 2020
2 stars
function mle(Y, A, C) {
let AT = math.transpose(A);
let X = math.multiply(math.inv(
math.multiply(math.multiply(AT, math.inv(C)), A)), math.multiply(math.multiply(AT, math.inv(C)), Y));
let covX = math.inv(math.multiply(math.multiply(AT, math.inv(C)), A));
return {X:X, covX:covX}
}
function fit_data (data) {
let Y = math.matrix(data.map( d=> [d.y] ))
let A = math.matrix(data.map( d => [ 1.0, d.x ] ))
let C = math.diag( data.map( d=>d.sigma_y * d.sigma_y ))
let result = mle(Y, A, C)
return result;
}
function pprint_result(result) {
return mtex`\vec{w} = \begin{bmatrix}b \\ m \end{bmatrix}= ${MatrixToTex(result.X)}\;\; \mathrm{cov}(\vec{w}) = ${MatrixToTex(result.covX)}`
}
r = fit_data(hoggdata)
pprint_result(r)
r1 = fit_data(hoggdata.filter(x => x.id>4))
pprint_result(r1)
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