This function extracts the fitted values from a model estimated with femlm
,
feols
or feglm
. The fitted values that are returned are the expected predictor.
Usage
# S3 method for fixest
fitted(object, type = c("response", "link"), na.rm = TRUE, ...)
# S3 method for fixest
fitted.values(object, type = c("response", "link"), na.rm = TRUE, ...)
Arguments
- object
A
fixest
object. Obtained using the functionsfemlm
,feols
orfeglm
.- type
Character either equal to
"response"
(default) or"link"
. Iftype="response"
, then the output is at the level of the response variable, i.e. it is the expected predictor \(E(Y|X)\). If"link"
, then the output is at the level of the explanatory variables, i.e. the linear predictor \(X\cdot \beta\).- na.rm
Logical, default is
TRUE
. IfFALSE
the number of observation returned will be the number of observations in the original data set, otherwise it will be the number of observations used in the estimation.- ...
Not currently used.
Value
It returns a numeric vector of length the number of observations used to estimate the model.
If type = "response"
, the value returned is the expected predictor, i.e. the
expected value of the dependent variable for the fitted model: \(E(Y|X)\).
If type = "link"
, the value returned is the linear predictor of the fitted model,
that is \(X\cdot \beta\) (remind that \(E(Y|X) = f(X\cdot \beta)\)).
Details
This function returns the expected predictor of a fixest
fit. The likelihood functions
are detailed in femlm
help page.
See also
See also the main estimation functions femlm
, feols
or feglm
.
resid.fixest
, predict.fixest
, summary.fixest
, vcov.fixest
, fixef.fixest
.
Examples
# simple estimation on iris data, using "Species" fixed-effects
res_poisson = femlm(Sepal.Length ~ Sepal.Width + Petal.Length +
Petal.Width | Species, iris)
# we extract the fitted values
y_fitted_poisson = fitted(res_poisson)
# Same estimation but in OLS (Gaussian family)
res_gaussian = femlm(Sepal.Length ~ Sepal.Width + Petal.Length +
Petal.Width | Species, iris, family = "gaussian")
y_fitted_gaussian = fitted(res_gaussian)
# comparison of the fit for the two families
plot(iris$Sepal.Length, y_fitted_poisson)
points(iris$Sepal.Length, y_fitted_gaussian, col = 2, pch = 2)