<s>
NLOGIT	B-Algorithm
is	O
an	O
extension	O
of	O
the	O
econometric	O
and	O
statistical	B-Algorithm
software	I-Algorithm
package	O
LIMDEP	B-Algorithm
.	O
</s>
<s>
In	O
addition	O
to	O
the	O
estimation	O
tools	O
in	O
LIMDEP	B-Algorithm
,	O
NLOGIT	B-Algorithm
provides	O
programs	O
for	O
estimation	O
,	O
model	O
simulation	O
and	O
analysis	O
of	O
multinomial	O
choice	O
data	O
,	O
such	O
as	O
brand	O
choice	O
,	O
transportation	O
mode	O
and	O
for	O
survey	O
and	O
market	O
data	O
in	O
which	O
consumers	O
choose	O
among	O
a	O
set	O
of	O
competing	O
alternatives	O
.	O
</s>
<s>
In	O
addition	O
to	O
the	O
economic	O
sciences	O
,	O
NLOGIT	B-Algorithm
has	O
applications	O
in	O
biostatistics	O
,	O
noneconomic	O
social	O
sciences	O
,	O
physical	O
sciences	O
,	O
and	O
health	O
outcomes	O
research	O
.	O
</s>
<s>
NLOGIT	B-Algorithm
was	O
released	O
in	O
1996	O
with	O
the	O
development	O
of	O
the	O
FIML	O
nested	O
logit	O
estimator	O
,	O
originally	O
an	O
extension	O
of	O
the	O
multinomial	O
logit	O
model	O
in	O
LIMDEP	B-Algorithm
.	O
</s>
<s>
With	O
the	O
additions	O
of	O
the	O
multinomial	B-General_Concept
probit	I-General_Concept
model	O
and	O
the	O
mixed	O
logit	O
model	O
among	O
several	O
others	O
,	O
NLOGIT	B-Algorithm
became	O
a	O
self	O
standing	O
superset	O
of	O
LIMDEP	B-Algorithm
.	O
</s>
<s>
NLOGIT	B-Algorithm
is	O
a	O
full	O
information	O
maximum	O
likelihood	O
estimator	O
for	O
a	O
variety	O
of	O
multinomial	O
choice	O
models	O
.	O
</s>
<s>
NLOGIT	B-Algorithm
includes	O
the	O
discrete	O
estimators	O
in	O
LIMDEP	B-Algorithm
plus	O
model	O
extensions	O
for	O
multinomial	O
logit	O
(	O
many	O
specifications	O
)	O
,	O
random	O
parameters	O
mixed	O
logit	O
,	O
random	O
regret	O
logit	O
,	O
WTP	O
space	O
specifications	O
in	O
mixed	O
logit	O
,	O
scaled	O
multinomial	O
logit	O
,	O
nested	O
logit	O
,	O
multinomial	B-General_Concept
probit	I-General_Concept
,	O
heteroscedastic	O
extreme	O
value	O
,	O
error	O
components	O
,	O
heteroscedastic	O
logit	O
and	O
latent	O
class	O
models	O
.	O
</s>
<s>
NLOGIT	B-Algorithm
is	O
typically	O
used	O
to	O
analyze	O
individual	O
,	O
cross	O
section	O
data	O
on	O
consumer	O
choices	O
and	O
decisions	O
from	O
multiple	O
alternatives	O
.	O
</s>
<s>
The	O
inference	O
tools	O
for	O
hypothesis	O
testing	O
include	O
the	O
Wald	B-General_Concept
,	O
likelihood	B-General_Concept
ratio	I-General_Concept
and	O
Lagrange	B-General_Concept
multiplier	I-General_Concept
tests	I-General_Concept
and	O
tools	O
for	O
discrete	O
choice	O
analysis	O
,	O
including	O
built-in	O
procedures	O
for	O
testing	O
the	O
IIA	O
assumption	O
of	O
the	O
multinomial	O
logit	O
model	O
.	O
</s>
<s>
The	O
models	O
estimated	O
by	O
NLOGIT	B-Algorithm
can	O
be	O
used	O
in	O
‘	O
what	O
if’	O
analyses	O
using	O
the	O
model	O
simulation	O
package	O
.	O
</s>
