fitted.fixest | R Documentation |
fixest
fitThis function extracts the fitted values from a model estimated with femlm
,
feols
or feglm
. The fitted values that are returned are the expected predictor.
## S3 method for class 'fixest'
fitted(object, type = c("response", "link"), na.rm = TRUE, ...)
## S3 method for class 'fixest'
fitted.values(object, type = c("response", "link"), na.rm = TRUE, ...)
object |
A |
type |
Character either equal to |
na.rm |
Logical, default is |
... |
Not currently used. |
This function returns the expected predictor of a fixest
fit. The likelihood functions
are detailed in femlm
help page.
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)
).
Laurent Berge
See also the main estimation functions femlm
, feols
or feglm
.
resid.fixest
, predict.fixest
, summary.fixest
, vcov.fixest
, fixef.fixest
.
# 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)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.