Description Usage Format References Examples
This is the simulated dataset used in Section 4.1 of Catania and Nonejad (2016).
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A matrix object containing 500 x 6 simulated observations.
Catania, Leopoldo, and Nima Nonejad (2018). "Dynamic Model Averaging for Practitioners in Economics and Finance: The eDMA Package." Journal of Statistical Software, 84(11), 1-39. doi: 10.18637/jss.v084.i11.
West, Mike. Bayesian forecasting. John Wiley & Sons, Inc., 1999.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | #the data set has been generated as:
set.seed(7892)
iT <- 500
iK <- 3
dV <- 0.1
mW <- diag(iK + 1) * 0.01
dPhi <- 1
vBeta0 <- rep(0, iK + 1)
mX <- cbind(1, matrix(rnorm(iT * (iK)), iT, iK))
lOut <- SimulateDLM(iT, mX, vBeta0, mW, dV, dPhi)
vY <- lOut$vY
mX <- mX[, -1]
iK_Add <- 2
mX_add <- matrix(rnorm(iT * iK_Add), iT, iK_Add)
SimData <- cbind(y = vY, mX, mX_add)
colnames(SimData) <- c("y", paste("x", 2:(iK + iK_Add + 1), sep = ""))
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