estimate.functional: Estimate Functional

In PointFore: Interpretation of Point Forecasts as State-Dependent Quantiles and Expectiles

Description

Estimates the parameter in a specification model for state-dependent quantile or expectile forecasts. For additional detail see the vignettes of the PointFore package.

Usage

estimate.functional(iden.fct = quantiles, model = constant,
  theta0 = NULL, Y, X, stateVariable = NULL, other_data = NULL,
  instruments = c("X", "lag(Y)"), prewhite = F, kernel = "Bartlett",
  bw = bwNeweyWest1987, ...)

Arguments

iden.fct	identification function. Standard choice is quantiles. The alternative is expectiles.
model	specification model. See constant for the simplest example and further suggestions.
theta0	starting value for optimization
Y	realized values
X	forecasts
stateVariable	state variable(s) as vector or matrix of column vectors.
other_data	optional for construction of instruments
instruments	instruments (list of character describing instruments or matrix of actual instruments). Use "const" for just the constant as instrument. Standard ist c("X","lag(Y)"), which uses the constant, the forecast and the lagged value of the outcome.
prewhite	logical or integer. Should the estimating functions be prewhitened? Standard is FALSE. If TRUE or greater than 0 a VAR model of order as.integer(prewhite) is fitted. (see ?gmm)
kernel	choose kernel for HAC-covariance estimation (see ?gmm). Standard is "Bartlett" Kernel as proposed in Newey and West (1987).
bw	function describing bandwidth selection (see ?gmm for alternatives). Standard is that the bandwidth depends on the sample length $T$ by $m(T)=T^1/5$.
...	other parameters for gmm function (see ?gmm)

Value

Object of type pointfore. Use summary and plot methods to illustrate results.

Examples

# estimate constant quantile level of GDP forecast
res <- estimate.functional(Y=GDP$observation, X=GDP$forecast,
model=constant)
summary(res)
plot(res)

# estimate constant quantile level with only the constant as instrument
res <- estimate.functional(Y=GDP$observation, X=GDP$forecast,
model=constant, instruments="const")
summary(res)

## Not run: 
# estimate constant expectile level
res <- estimate.functional(Y=GDP$observation, X=GDP$forecast,
model=constant, instruments="const", iden.fct = expectiles)
summary(res)
plot(res)

# estimate state-dependent quantile level with linear probit specification model
res <- estimate.functional(Y=GDP$observation, X=GDP$forecast,
stateVariable = GDP$forecast, model = probit_linear)
summary(res)
plot(res)

## End(Not run)

PointFore documentation built on May 2, 2019, 9:42 a.m.