Created
September 5, 2017 14:25
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source("common.R", encoding = "utf-8") | |
# ---- dlm ------ | |
# model 3 | |
res <- data.frame() | |
for( a in seq(from=.1, to=.95, by=.05) ){ | |
RP <- calc_RP(RP = df$RP095, p = df$AP, a = a) | |
z <- calc_Z(RP = RP, p = df$AP) | |
z1 <- z$z1 | |
z2 <- z$z2 | |
z1E <- z$z1 * df$end | |
z2E <- z$z2 * df$end | |
# create the design matrix | |
regressors <- cbind(z1, z1E, z2, z2E) | |
# model settings | |
# params[1] = obs. noise variance | |
# params[2] = local trend noise variance | |
# params[3:6] = noises variance of alpha_1, beta_1, alpha_2, beta_2 | |
# params[7:8] = AR coefs | |
# params[9] = AR(2) noise variance | |
buildModel3 <- function(params){ | |
model <- dlmModReg(regressors, addInt = F, | |
dV = exp(params[1]), dW = exp(params[3:6])) + # time-varying regression | |
dlmModPoly(order=1, dW = exp(params[2])) + # time-varying intercept | |
dlmModARMA(ar=c(tanh(params[7]), tanh(params[8])), sigma=exp(params[9])) # AR(2) component | |
return(model) | |
} | |
# estimate structural params | |
e <- try({res.mle <- dlmMLE(df$logPI, rep(0, 9), buildModel3, method = "L-BFGS-B", hessian=T, | |
control = list(maxit = 1000000, trace=1)) | |
}) | |
if (class(e) == "try-error") { | |
} | |
else { | |
res <- bind_rows(res, | |
data.frame( | |
a=a, | |
conv=res.mle$convergence, loglike=-res.mle$value, | |
AIC=2*res.mle$value+2*10, | |
matrix(res.mle$par, nrow=1)) | |
) | |
} | |
} | |
res[,5:10] <- exp(res[,5:10]) | |
res[,11:12] <- tanh(res[,11:12]) | |
res[,13] <- exp(res[,13]) | |
(result <- filter(res, conv == 0) %>% arrange(desc(loglike))) | |
a <- result$a[1] | |
RP <- calc_RP(RP = df$RP095, p = df$AP, a = a) | |
z <- calc_Z(RP = RP, p = df$AP) | |
# create the design matrix | |
x<-cbind(z$z1, z$z2, z$z1 * df$end, z$z2 * df$end) | |
parameters <- result[1,5:ncol(res)] %>% as.numeric | |
print(paste("AIC=", round(2*result$loglike[1]+2*(ncol(res) - 4), 2))) | |
# filtering | |
mod3 <- buildModel3(parameters) | |
mod.filt3 <- dlmFilter(df$logPI, mod3) | |
# smoothing | |
mod.smooth3 <- dlmSmooth(mod.filt3) | |
# plot smoothed parameters | |
df.params <- data.frame(dropFirst(mod.smooth3$s[,1:7])) | |
colnames(df.params) <- c("alpha1", "beta1", "alpha2", "beta2", "c", "phi1", "phi2") | |
df.params$t <- 1:nrow(df.params) | |
df.params <- gather(df.params, key=series, value=value, -t) | |
ggplot(df.params) + geom_line(aes(x=t, y=value, group=series), color="grey") + | |
facet_wrap(~series, scales = "free") + scale_color_discrete(guide=F) + | |
labs(x="week", y="") + theme_bw() |
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