setParameters <- function(){
# parameters
skipList <- c(51, 217, 218, 493, 494, 223, 442, 548, 549, 550, 551,
552, 553, 554, 555, 556, 557, 558, 559)
nObjects <- 1001
numGen <- 100
maxCluster <- 3
numFitSources<- 7
weakLinkPercent <- 0.005
permuteParam <- c(0.9, 0.3) # two paramters, first for model switching, second for Box Cox switching
freqList <- tibble(
freq = c(1, 4, 12),
named = c("annual", "quarterly", "monthly")
)
# list of things in the metadata for each series
IC <- c("AIC", "AICc", "BIC", "HQ", "RSS")
measures <- c("MAPE", "MASE", "MdAPE", "MdASE")
features <- c("frequency", "trend", "seasonal", "autocorrelation",
"non-linear", "skewness",
"kurtosis", "Hurst", "Lyapunov",
"dc autocorrelation", "dc non-linear", "dc skewness",
"dc kurtosis")
meta <- c("clusterNumber", "rank", "gensSinceImprovement",
"modelChoice")
features <- c(IC, measures, features, meta)
modelList <- list(
arima = function(x) auto.arima(x, stepwise=FALSE, approximation=FALSE),
nnetar = function(x) nnetar(x),
meanforecast = function(x) meanf(x, h),
naive = function(x) rwf(x, h),
seasonalNaive = function(x) snaive(x, h),
rwDrift = function(x) rwf(x, h, drift=TRUE),
simpleExpSmoothing = function(x) ses(x, h),
holtMethod = function(x) holt(x, h),
holtDamped = function(x) holt(x, damped = TRUE, phi = 0.9, h),
hwSeasonalAdditive = function(x) hw(x, seasonal = "additive"),
hwSeasonalMultiplicative = function(x) hw(x, seasonal = "multiplicative"),
hwDSeasonalAdditive = function(x) hw(x, seasonal = "additive", damped = TRUE),
hwDSeasonalMultiplicative = function(x) hw(x, seasonal = "multiplicative", damped = TRUE),
bagETS = function(x) baggedETS(x)
)
h = 5
lastSlot <- length(features)
returnList <- list("skipList" = skipList,
"nObjects" = nObjects,
"numGen" = numGen,
"maxCluster" = maxCluster,
"numFitSources" = numFitSources,
"weakLinkPercent" = weakLinkPercent,
"permuteParam" = permuteParam,
"features" = features,
"freqList" = freqList,
"modelList" = modelList,
"h" = h,
"lastSlot" = lastSlot)
return(returnList)
}
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