Model-based least squares, closed form cross-checked against descent (Geron Ch 1, morie.fn hmmod)

Usage

morie_geron_model_based(X, y, add_bias = TRUE, eta = NULL, n_iter = 1000)

Arguments

X, y: Data.
add_bias: Prepend ones column.
eta: Optional learning rate.
n_iter: Descent iterations.

Value

List with theta, theta_gd, mse, r2, gap, eta, estimate, n, method.

Examples

V <- c(1, 2, 3, 4, 5, 6, 7, 8)
morie_geron_model_based(V, V)
#> $theta
#> [1] 1.128963e-15 1.000000e+00
#> 
#> $theta_gd
#> [1] 8.467236e-05 9.999849e-01
#> 
#> $mse
#> [1] 2.372746e-30
#> 
#> $r2
#> [1] 1
#> 
#> $gap
#> [1] 8.600125e-05
#> 
#> $eta
#> [1] 0.01901113
#> 
#> $residuals
#> [1]  6.661338e-16  4.440892e-16  0.000000e+00 -4.440892e-16 -8.881784e-16
#> [6] -1.776357e-15 -2.664535e-15 -2.664535e-15
#> 
#> $n_parameters
#> [1] 2
#> 
#> $estimate
#> [1] 2.372746e-30
#> 
#> $n
#> [1] 8
#> 
#> $method
#> [1] "Model-based fit (least squares, closed form and by descent)"
#>