curvir (version 0.1.1)

plot.curvir: Plot method for curvir reserve demand models

Description

Plot a reserve demand curve estimated using curve.

Plot a non-parametric reserve demand curve estimated using npcurve.

Usage

# S3 method for curvir
plot(
  x,
  ploty = c(FALSE, TRUE),
  plotq = c(TRUE, FALSE),
  usemean = c(FALSE, TRUE),
  prcmp = c(FALSE, TRUE),
  useline = c(FALSE, TRUE),
  main = NULL,
  pch = 20,
  ...
)
# S3 method for npcurvir
plot(
  x,
  ploty = c(FALSE, TRUE),
  plotq = c(TRUE, FALSE),
  usemean = c(FALSE, TRUE),
  prcmp = c(FALSE, TRUE),
  useline = c(FALSE, TRUE),
  main = NULL,
  pch = 20,
  ...
)

Value

No returned value. Produces a plot of the estimated curve.

Arguments

x

A model fit with curve.

ploty

Logical (TRUE or FALSE) to plot data used for fitting or not.

plotq

Logical (TRUE or FALSE) to plot intervals.

usemean

Logical (TRUE or FALSE) to replace all explanatory variables (except from excess reserves) with their mean. It cannot be used if a dummy is used in the fitting of the curve.

prcmp

Logical (TRUE or FALSE) to use principal components to project all variables into two dimensions. Requires usemean == FALSE. This may be useful when multiple explanatory variables are used.

useline

Logical (TRUE or FALSE) to force line plots when usemean == FALSE or prcomp == FALSE and there are many explanatory variables.

main

Use to overide the default plot title.

pch

Use to overide the dafault marker type for points.

...

Additional inputs (currently unused).

Methods (by class)

• plot(curvir): Plot parametric curves

• plot(npcurvir): Plot non-parametric curves

Author

Nikolaos Kourentzes,

References

Chen, Z., Kourentzes, N., & Veyrune, R. (2023). Modeling the Reserve Demand to Facilitate Central Bank Operations. IMF Working Papers, 2023(179).

See Also

curve.

npcurve.

Examples

# \dontshow{
  rate <- head(ecb$rate,10)
  x <- ecb$x[1:10,1,drop=FALSE]
  fit <- curve(x,rate,rep=1,type="fixExponential")
  plot(fit)
# }
# \donttest{
  # Use ECB example data
  rate <- ecb$rate
  x <- ecb$x[,1,drop=FALSE]
  fit <- curve(x,rate)
  plot(fit)
# }

# Use ECB example data
rate <- ecb$rate
x <- ecb$x[,1,drop=FALSE]
fit <- npcurve(x,rate)
plot(fit)