如何使用R來強化bst的結果？

Question

bsts是貝葉斯結構time series modeling的R包。

library(bsts) 
# Load data 
data(iclaims) 
#Specify the trend and seasonality. 
ss <- AddLocalLinearTrend(list(), initial.claims$iclaimsNSA) 
ss <- AddSeasonal(ss, initial.claims$iclaimsNSA, nseasons = 52) 
#set the seed within bsts. 
model2 <- bsts(iclaimsNSA ~ ., state.specification = ss, data = 
          initial.claims, niter = 3000, seed = 1) 
model3 <- bsts(iclaimsNSA ~ ., state.specification = ss, data = 
          initial.claims, niter = 3000, seed = 1) 
# plot the results 
par(mfrow=c(2, 2)) 
plot(model2, "coefficients") 
plot(model3, "coefficients") 
plot(model2, "size") 
plot(model3, "size") 

結果由上面的圖中給出。顯然，即使我們設置了bsts的種子並將迭代次數增加到3000，這兩個結果也不完全相同。

我也試過從bsts中set.seed（）。它也不起作用。

set.seed(1); model2 <- bsts(iclaimsNSA ~ ., state.specification = ss, data = 
          initial.claims, niter = 3000, seed = 1) 
set.seed(1); model3 <- bsts(iclaimsNSA ~ ., state.specification = ss, data = 
          initial.claims, niter = 3000, seed = 1) 

Answer 1

你應該check參數burn在predict.bsts。也可以玩SuggestBurn功能。希望有所幫助。