residuals: Extract Model Residuals In npreg: Nonparametric Regression via Smoothing Splines

 residuals R Documentation

Extract Model Residuals

Description

Extracts the residuals from a fit smoothing spline ("ss"), smooth model ("sm"), or generalized smooth model ("gsm") object.

Usage

```## S3 method for class 'ss'
residuals(object, type = c("working", "response", "deviance",
"pearson", "partial"), ...)

## S3 method for class 'sm'
residuals(object, type = c("working", "response", "deviance",
"pearson", "partial"), ...)

## S3 method for class 'gsm'
residuals(object, type = c("deviance", "pearson", "working",
"response", "partial"), ...)
```

Arguments

 `object` an object of class "ss", "sm", or "gsm" `type` type of residuals `...` other arugments (currently ignored)

Details

For objects of class `ss` and `sm`
* the working and response residuals are defined as 'observed - fitted'
* the deviance and Pearson residuals multiply the working residuals by `sqrt(weights(object))`

For objects of class `gsm`, the residual types are the same as those produced by the `residuals.glm` function

Value

Residuals from `object`

Author(s)

Nathaniel E. Helwig <helwig@umn.edu>

References

Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.

Helwig, N. E. (2020). Multiple and Generalized Nonparametric Regression. In P. Atkinson, S. Delamont, A. Cernat, J. W. Sakshaug, & R. A. Williams (Eds.), SAGE Research Methods Foundations. doi: 10.4135/9781526421036885885

`ss`, `sm`, `gsm`

Examples

```# generate data
set.seed(1)
n <- 100
x <- seq(0, 1, length.out = n)
fx <- 2 + 3 * x + sin(2 * pi * x)
y <- fx + rnorm(n, sd = 0.5)

# smoothing spline
mod.ss <- ss(x, y, nknots = 10)
res.ss <- residuals(mod.ss)

# smooth model
mod.sm <- sm(y ~ x, knots = 10)
res.sm <- residuals(mod.sm)

# generalized smooth model (family = gaussian)
mod.gsm <- gsm(y ~ x, knots = 10)
res.gsm <- residuals(mod.gsm)

# y = fitted + residuals
mean((y - fitted(mod.ss) - res.ss)^2)
mean((y - fitted(mod.sm) - res.sm)^2)
mean((y - fitted(mod.gsm) - res.gsm)^2)
```

npreg documentation built on July 21, 2022, 1:06 a.m.