xu-lisa
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R/penalize-laglead.R
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| 1 | + | smooth.construct.fdl.smooth.spec <- function(object, data, knots) { |
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| 2 | + | ||
| 3 | + | # modify object so that it's fitted as a p-spline signal regression term: |
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| 4 | + | object$bs <- "ps" |
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| 5 | + | object <- smooth.construct.ps.smooth.spec(object, data, knots) |
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| 6 | + | ||
| 7 | + | if (!is.null(object$xt$fullrankpen) && object$xt$fullrankpen) { |
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| 8 | + | # add ridge penalty to first <order of B-spline>+1 (=m+2) basis functions with |
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| 9 | + | # same variance as difference penalty : penalty = lambda * coef' (DiffPen + |
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| 10 | + | # RidgePen) coef |
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| 11 | + | object$S[[1]][cbind(1:(object$m[1] + 2), 1:(object$m[1] + 2))] <- object$S[[1]][cbind(1:(object$m[1] + 2), |
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| 12 | + | 1:(object$m[1] + 2))] + 1 |
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| 13 | + | object$rank <- min(object$bs.dim, object$rank + object$m[1] + 2) |
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| 14 | + | } |
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| 15 | + | if (!is.null(object$xt$ridge) && object$xt$ridge) { |
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| 16 | + | # add lag-lead penalty to first and last <order of B-spline>+1 (=m+2) basis functions penalty |
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| 17 | + | # = coef' (lambda_1*DiffPen + lambda_2*LagLeadPen) coef |
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| 18 | + | if (!is.null(object$xt$leadpen) && !is.null(object$xt$lagpen) && object$xt$leadpen && object$xt$lagpen) { |
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| 19 | + | object$S[[2]] <- matrix(0, object$bs.dim, object$bs.dim) |
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| 20 | + | # penalize lead |
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| 21 | + | object$S[[2]][cbind(1:(object$m[1] + 2), 1:(object$m[1] + 2))] <- 1 |
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| 22 | + | # penalize lag |
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| 23 | + | object$S[[2]][cbind((object$bs.dim - (object$m[1] + 2) + 1): object$bs.dim, |
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| 24 | + | (object$bs.dim - (object$m[1] + 2) + 1): object$bs.dim)] <- 1 |
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| 25 | + | ||
| 26 | + | object$rank <- c(object$rank, min(2*(object$m[1] + 2), object$bs.dim)) |
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| 27 | + | } |
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| 28 | + | else if (!is.null(object$xt$leadpen) && object$xt$leadpen) { |
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| 29 | + | # add ridge penalty (lead penalty) to first <order of B-spline>+1 (=m+2) basis functions penalty |
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| 30 | + | # = coef' (lambda_1*DiffPen + lambda_2*RidgePen) coef |
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| 31 | + | object$S[[2]] <- matrix(0, object$bs.dim, object$bs.dim) |
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| 32 | + | object$S[[2]][cbind(1:(object$m[1] + 2), 1:(object$m[1] + 2))] <- 1 |
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| 33 | + | object$rank <- c(object$rank, object$m[1] + 2) |
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| 34 | + | } |
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| 35 | + | else if (!is.null(object$xt$lagpen) && object$xt$lagpen) { |
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| 36 | + | # add lag penalty to last <order of B-spline>+1 (=m+2) basis functions penalty |
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| 37 | + | # = coef' (lambda_1*DiffPen + lambda_2*LagPen) coef |
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| 38 | + | object$S[[2]] <- matrix(0, object$bs.dim, object$bs.dim) |
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| 39 | + | object$S[[2]][cbind((object$bs.dim - (object$m[1] + 2) + 1): object$bs.dim, |
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| 40 | + | (object$bs.dim - (object$m[1] + 2) + 1): object$bs.dim)] <- 1 |
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| 41 | + | object$rank <- c(object$rank, object$m[1] + 2) |
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| 42 | + | } |
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| 43 | + | } |
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| 44 | + | if (!is.null(object$xt$constrain) && object$xt$constrain) { |
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| 45 | + | # constrain to end in zero (i.e (X%*%coefficients)[1] == 0) --> |
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| 46 | + | # Constraint matric C = X[1,] |
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| 47 | + | object$C <- matrix(object$X[1, ], nrow = 1) |
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| 48 | + | object$C <- structure(object$C, always.apply = TRUE) |
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| 49 | + | } |
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| 50 | + | ||
| 51 | + | return(object) |
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| 52 | + | ||
| 53 | + | } |
| Files | Coverage |
|---|---|
| R | 91.94% |
| Project Totals (28 files) | 91.94% |
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