@intercept |

Intercept from trend regression.

Syntax: @intercept(m)

m: matrix, vector

Return: number

Returns the intercept of an OLS regression on matrix or vector m versus a constant and an implicit time trend, as in @detrend.

When applied to a matrix, the matrix elements are arranged in vectorization order and then paired with the implicit time trend.

Examples

We begin by creating a workfile, generating a random series, and then converting to a vector so that we can compute identical results using the series and the vector.

workfile u 100

series y = nrnd

vector yv = @convert(y)

The trend regression intercept estimate is given by

scalar icpt1 = @intercept(yv)

Alternately, the trend regression results may be obtained using the vector YV using the @regress command on the augmented data matrix:

matrix vcoefs = @regress(@hcat(yv, @ones(yv.@rows), @range(0, yv.@rows-1))

The first column of VCOEFS contains the intercept and trend coefficients, so

scalar icpt2 = vcoefs(1)

is the intercept.

Estimates may also be obtained using the series and an equation object

equation eq1.ls y c @trend

scalar icpt3 = eq1.c(1)

Cross-references