InputsForMLEdensity {MultiATSM} | R Documentation |
Generates several inputs that are necessary to build the likelihood function
Description
Generates several inputs that are necessary to build the likelihood function
Usage
InputsForMLEdensity(
ModelType,
Yields,
PdynamicsFactors,
FactorLabels,
mat,
Economies,
DataFrequency,
JLLinputs = NULL,
GVARinputs = NULL,
BRWinputs = NULL
)
Arguments
ModelType |
string-vector containing the label of the model to be estimated |
Yields |
time series of yields (JxT or CJ x T) |
PdynamicsFactors |
time series of the risk factors (K x T) |
FactorLabels |
string-list based which contains the labels of all variables present in the model |
mat |
vector of maturities (in years) used in the estimation |
Economies |
string-vector containing the names of the economies of the system. |
DataFrequency |
character-based-vector. Avaialable options are: "Daily All Days", "Daily Business Days", "Weekly", "Monthly", "Quarterly", "Annually" |
JLLinputs |
list of necessary inputs for the estimation of JLL-based models (see "JLL" function) |
GVARinputs |
list of necessary inputs for the estimation of GVAR-based models (see "GVAR" function) |
BRWinputs |
list of necessary inputs for performing the bias-corrected estimation (see "Bias_Correc_VAR" function) |
Details
To ensure that the risk factors matrix is correctly built for the model "JPS", the global factors should be allocated on the first G rows of this matrix.
Value
List of necessary inputs for constructing the model's log-likelihood function
Examples
# Example 1:
data(CM_Factors)
data(CM_Yields)
ModelType <- "JPS"
Economies <- "Mexico"
Factors <- RiskFactors
N <- 3
GlobalVar <- c("GBC", "CPI_OECD") # Global Variables
DomVar <- c("Eco_Act", "Inflation") # Domestic Variables
FactorLabels <- LabFac(N, DomVar,GlobalVar, Economies, ModelType)
mat <- c(0.25, 0.5, 1, 3, 5, 10)
DataFrequency <- "Monthly"
i <- length(Economies)
ATSMInputs <- InputsForMLEdensity(ModelType, Yields, Factors, FactorLabels, mat,
Economies, DataFrequency)
# Example 2:
data(CM_Factors)
data(CM_Yields)
data(CM_Factors_GVAR)
ModelType <- "GVAR jointQ"
Economies <- c("China", "Brazil", "Mexico", "Uruguay")
mat <- c(0.25, 0.5, 1, 3, 5, 10)
DataFrequency <- "Monthly"
Factors <- RiskFactors
N <- 3
GlobalVar <- c("GBC", "CPI_OECD") # Global Variables
DomVar <- c("Eco_Act", "Inflation") # Domestic Variables
FactorLabels <- LabFac(N, DomVar,GlobalVar, Economies, ModelType)
GVARinputs <- list()
GVARinputs$Economies <- Economies
GVARinputs$GVARFactors <- FactorsGVAR
GVARinputs$VARXtype <- "unconstrained"
GVARinputs$Wgvar <- matrix( c(0, 0.83, 0.86, 0.38,
0.65, 0, 0.13, 0.55,
0.32, 0.12, 0, 0.07,
0.03, 0.05, 0.01, 0), nrow = 4, ncol = 4)
ATSMInputs <- InputsForMLEdensity(ModelType, Yields, Factors, FactorLabels, mat, Economies,
DataFrequency, JLLinputs= NULL , GVARinputs)
# Example 3:
if (requireNamespace('neldermead', quietly = TRUE)) {
data(CM_Factors)
data(CM_Yields)
ModelType <- "JLL jointSigma"
GlobalVar <- c("GBC", "CPI_OECD") # Global Variables
DomVar <- c("Eco_Act", "Inflation") # Domestic Variables
N <- 3
Economies <- c( "China", "Brazil", "Mexico", "Uruguay")
FactorLabels <- LabFac(N, DomVar, GlobalVar, Economies, ModelType)
Factors <- RiskFactors
mat <- c(0.25, 0.5, 1, 3, 5, 10)
DataFrequency <- "Monthly"
JLLinputs <- list()
JLLinputs$Economies <- Economies
JLLinputs$DomUnit <- "China"
JLLinputs$WishSigmas <- 1
JLLinputs$SigmaNonOrtho <- NULL
JLLinputs$JLLModelType <- ModelType
ATSMInputs <- InputsForMLEdensity(ModelType, Yields, Factors, FactorLabels, mat, Economies,
DataFrequency, JLLinputs)
} else {
message("skipping functionality due to missing Suggested dependency")
}