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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,45 +1,90 @@ | ||
| "SZ.prior.evaluation" <- function(Y, p, lambda0, lambda1, lambda3, | ||
| lambda4, lambda5, mu5, mu6, z=NULL, nu=ncol(Y)+1, qm, prior=0, | ||
| nstep, y.future) | ||
| { combos <- length(lambda0)*length(lambda1)*length(lambda3)*length(lambda4) | ||
| results <- matrix(0, combos ,11) | ||
| h <- 0 | ||
|
|
||
| for(i in 1:length(lambda0)) | ||
| { for(j in 1:length(lambda1)) | ||
| { for(k in 1:length(lambda3)) | ||
| { for(l in 1:length(lambda4)) | ||
| { fit <- szbvar(Y, p, z, | ||
| lambda0[i], | ||
| lambda1[j], | ||
| lambda3[k], | ||
| lambda4[l], | ||
| lambda5=lambda5, | ||
| mu5=mu5, | ||
| mu6=mu6, | ||
| nu=nu, | ||
| qm=qm, | ||
| prior=prior, | ||
| posterior.fit=T) | ||
|
|
||
| forecast <- forecast.VAR(fit, nstep) | ||
| eval.forecasts <- | ||
| cf.forecasts(forecast[(nrow(forecast)-nstep+1):nrow(forecast),], y.future) | ||
|
|
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| # Now gather up all the parameters and results | ||
| tmp <- c(lambda0[i],lambda1[j],lambda3[k],lambda4[l], | ||
| lambda5, mu5, mu6, eval.forecasts[1], | ||
| eval.forecasts[2], fit$marg.llf[1], | ||
| fit$marg.post[1]) | ||
|
|
||
| h <- h+1 | ||
| results[h,] <- tmp | ||
|
|
||
| }}}} | ||
|
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||
| colnames(results) <- c("lambda0", "lambda1", "lambda3", "lambda4", | ||
| "lambda5", "mu5", "mu6", "RMSE", "MAE", "MargLLF", | ||
| "MargPosterior") | ||
| # New version of this -- optimized for speed and more values of the | ||
| # hyperparameters | ||
|
|
||
| SZ.prior.evaluation <- function (Y, p, lambda0, lambda1, lambda3, lambda4, lambda5, | ||
| mu5, mu6, z = NULL, nu = ncol(Y) + 1, qm, prior = 0, nstep, | ||
| y.future) | ||
| { | ||
| combos <- length(lambda0) * length(lambda1) * length(lambda3) * | ||
| length(lambda4) * length(lambda5) * length(mu5) * length(mu6) | ||
|
|
||
| results <- matrix(0, combos, 11) | ||
|
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| results[,1:7] <- as.matrix(expand.grid(lambda0=lambda0, lambda1=lambda1, | ||
| lambda3=lambda3, lambda4=lambda4, | ||
| lambda5=lambda5, mu5=mu5, mu6=mu6)) | ||
|
|
||
| for (i in 1:nrow(results)) | ||
| { | ||
| fit <- szbvar(Y, p, z, lambda0=results[i,1], | ||
| lambda1=results[i,2], | ||
| lambda3=results[i,3], lambda4=results[i,4], | ||
| lambda5 = results[i,5], | ||
| mu5 = results[i,6], mu6 = results[i,7], nu = | ||
| ncol(Y)+1, qm = qm, prior = prior, | ||
| posterior.fit = T) | ||
|
|
||
| forecast <- forecast.VAR(fit, nstep) | ||
| eval.forecasts <- cf.forecasts(forecast[(nrow(forecast) - | ||
| nstep + 1):nrow(forecast), ], y.future) | ||
|
|
||
| tmp <- c(eval.forecasts[1], eval.forecasts[2], fit$marg.llf[1], fit$marg.post[1]) | ||
|
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| results[i, 8:11] <- tmp | ||
|
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| if(i%%100==T) { cat("Finished model", i, "of", nrow(results),"\n") } | ||
|
|
||
| } | ||
| colnames(results) <- c("lambda0", "lambda1", "lambda3", "lambda4", | ||
| "lambda5", "mu5", "mu6", "RMSE", "MAE", "LLF", "logMDD") | ||
| return(results) | ||
| } | ||
| } | ||
|
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||
|
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|
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| ## "SZ.prior.evaluation" <- function(Y, p, lambda0, lambda1, lambda3, | ||
| ## lambda4, lambda5, mu5, mu6, z=NULL, nu=ncol(Y)+1, qm, prior=0, | ||
| ## nstep, y.future) | ||
| ## { combos <- length(lambda0)*length(lambda1)*length(lambda3)*length(lambda4) | ||
| ## results <- matrix(0, combos ,11) | ||
| ## h <- 0 | ||
|
|
||
| ## for(i in 1:length(lambda0)) | ||
| ## { for(j in 1:length(lambda1)) | ||
| ## { for(k in 1:length(lambda3)) | ||
| ## { for(l in 1:length(lambda4)) | ||
| ## { fit <- szbvar(Y, p, z, | ||
| ## lambda0[i], | ||
| ## lambda1[j], | ||
| ## lambda3[k], | ||
| ## lambda4[l], | ||
| ## lambda5=lambda5, | ||
| ## mu5=mu5, | ||
| ## mu6=mu6, | ||
| ## nu=nu, | ||
| ## qm=qm, | ||
| ## prior=prior, | ||
| ## posterior.fit=T) | ||
|
|
||
| ## forecast <- forecast.VAR(fit, nstep) | ||
| ## eval.forecasts <- | ||
| ## cf.forecasts(forecast[(nrow(forecast)-nstep+1):nrow(forecast),], y.future) | ||
|
|
||
| ## # Now gather up all the parameters and results | ||
| ## tmp <- c(lambda0[i],lambda1[j],lambda3[k],lambda4[l], | ||
| ## lambda5, mu5, mu6, eval.forecasts[1], | ||
| ## eval.forecasts[2], fit$marg.llf[1], | ||
| ## fit$marg.post[1]) | ||
|
|
||
| ## h <- h+1 | ||
| ## results[h,] <- tmp | ||
|
|
||
| ## }}}} | ||
|
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| ## colnames(results) <- c("lambda0", "lambda1", "lambda3", "lambda4", | ||
| ## "lambda5", "mu5", "mu6", "RMSE", "MAE", "MargLLF", | ||
| ## "MargPosterior") | ||
|
|
||
| ## return(results) | ||
| ## } |
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