probit {micEcon} | R Documentation |
The functions calculates probit binary choice model
probit(formula, b0 = NULL, data = sys.frame(sys.parent()), x=FALSE, y = FALSE, model = FALSE, method="ML", ... )
formula |
a symbolic description of the model to be fit in the
form response ~ explanatory variables . The
response variable should be either logical or numeric with values
only 0-1. See
e.g. lm for details. |
b0 |
inital value of parameters. |
data |
an optional data frame containing the variables in the
model. If not found in data, the
variables are taken from environment(formula), typically the
environment from which probit is called. |
x, y, model |
logicals. If TRUE the corresponding components of the fit (the model matrix, the response, the model frame) are returned. |
method |
the method to be used; for fitting, currently only method = "ML" (Maximum Likelihood) is supported; method = "model.frame" returns the model frame (the same as with model = TRUE, see below). |
... |
further arguments for maxLik . |
The model is estimated using Maximum Likelihood method.
An object of class "probit". It is a list with following components:
LRT |
Likelihood ration test. The full model is tested against
H0: the parameters have no effect on the result. This is a list
with components
|
NParam |
Number of parameters of the model including constant |
NObs |
Number of the observations |
N1 |
Number of observations with non-zero (true) response |
N0 |
Number of observations with zero (false) response |
df |
Number of free parameters |
x |
if requested, the model matrix used. |
y |
if requested, the response used. |
model |
if requested, the model frame used. |
Other components are inherited from maxLik
.
Ott Toomet otoomet@ut.ee
W. Greene: Advanced Econometrics, 2000, p ....
maxLik
for ready-packaged likelihood maximisation
routines and methods, glm
for generalised linear models,
including probit, binomial
.
## A simple MC trial: note probit assumes normal errors x <- runif(100) e <- 0.5*rnorm(100) y <- x + e summary(probit((y > 0) ~ x)) ## female labour force participation probability data(Mroz87) Mroz87$kids <- Mroz87$kids5 > 0 | Mroz87$kids618 > 0 Mroz87$age30.39 <- Mroz87$age < 40 Mroz87$age50.60 <- Mroz87$age >= 50 summary(probit(lfp ~ kids + age30.39 + age50.60 + educ + hushrs + huseduc + huswage + mtr + motheduc, data=Mroz87))