# invcurve: Calculate the inverse curve prediction In curvir: Specify Reserve Demand Curves

 invcurve R Documentation

## Calculate the inverse curve prediction

### Description

Calculate the predicted reserves given some rate, i.e., calculate the prediction of the inverse curve.

### Usage

``````invcurve(
object,
ynew = NULL,
xnew = NULL,
dummynew = NULL,
warn = c(TRUE, FALSE)
)
``````

### Arguments

 `object` A model fit with `curve`. `ynew` The input rate. If `NULL` this corresponds to the values from `predict(object)`. `xnew` The values for the additional regressors that were used in the curve fit. Must be a matrix, ordered (columns) as they were input in the fitting of the curve. The constant is dealt with automatically. Do not input the excess reserves. If `NULL` this is picked up from the data used to fit the curve. `dummynew` The values for the indicator, if one was used in the fitting of the curve. If `NULL` then the data used in the fitting of the model are used. `warn` A logical (`TRUE` or `FALSE`) to issue a warning if the resulting values are more than 10% away from the min-max of the excess reserves used to estimate the curve.

### Value

Returns a vector of values of the predicted reserves

### Author(s)

Nikolaos Kourentzes, nikolaos@kourentzes.com

### References

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

`curve`, and `predict`.

### Examples

``````

# Use ECB example data
rate <- ecb\$rate
x <- ecb\$x[,1,drop=FALSE]
fit <- curve(x,rate,type="logistic")
invcurve(fit)

# Use a different input rate
invcurve(fit,ynew=0.1)

``````

curvir documentation built on Nov. 24, 2023, 5:09 p.m.