computer science

NLOGIT

NLOGIT is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand NLOGIT rather than just read about it. In short: NLOGIT is a stand-alone extension of the econometric software package LIMDEP. It adds estimation, simulation and diagnostic tools for multinomial discrete-choice models—ranging from basic multinomial logit to mixed logit, random-regret logit, nested logit and latent-class specifications.

Key takeaways

NLOGIT belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect NLOGIT to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of NLOGIT from memory before moving on to harder problems.

Reference excerpt

NLOGIT is a stand-alone extension of the econometric software package LIMDEP. It adds estimation, simulation and diagnostic tools for multinomial discrete-choice models—ranging from basic multinomial logit to mixed logit, random-regret logit, nested logit and latent-class specifications. Although first targeted at economists, NLOGIT is now cited in studies across the social sciences, public health, transportation and marketing. Recent applied work still relies on version 6, released in 2016, because no further updates have appeared since the developer announced its closure in 2024.

History Econometric Software, Inc. was founded in the early 1980s by NYU economist William H. Greene. An experimental “DISCRETE CHOICE” command in LIMDEP 6.0 (1994) evolved into a separate product: NLOGIT 1.0 (1996), whose core feature was a full‐information nested-logit estimator. Over the next two decades the program grew into a superset of LIMDEP, adding multinomial probit, mixed logit and a graphical simulation interface. On 1 November 2024 an official notice on the company’s website (mirrored by regional reseller SoftHome International) stated: “After 35 years of developing and providing pioneering tools for micro-econometric analysis, Econometric Software, Inc. is closing its operations. We wholeheartedly thank all our users …”. Since that announcement the main domains limdep.com and nlogit.com have gone offline, and version 6 (build 10.0.12) remains the final release.

Models NLOGIT implements full-information maximum-likelihood or simulated-likelihood estimators for a wide range of choice models. Among them are:

Unrestricted and scaled multinomial logit models, including heteroscedastic variants. Mixed logit (a.k.a. random-parameters logit) with flexible distributional assumptions. Random-regret logit and “willingness-to-pay-space’’ parameterisations. Nested logit, heteroscedastic extreme value and error-components logit. Multinomial probit with simulation-based integration. Latent class models for unobserved taste heterogeneity.

Data analysis and simulation A project interface lets users combine data management, model estimation and “what-if’’ market-share simulations in one session. Probability forecasts from the fitted model can be recomputed under counter-factual scenarios—such as price changes or policy interventions—either for the original sample or for any compatible external dataset.

Current status Since the 2024 closure of Econometric Software, NLOGIT is no longer sold or supported, and the official download servers are offline. Existing licence holders can still run version 6 on modern Windows systems, but new users typically adopt open-source alternatives (e.g. Python Biogeme or R gmnl) that replicate most NLOGIT functionality.

See also List of statistical packages Comparison of statistical packages LIMDEP

References

Worked examples

Example 1 — a first encounter with NLOGIT

Start with the simplest possible case. Write down what NLOGIT claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to NLOGIT before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about NLOGIT ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of NLOGIT

In research: NLOGIT appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses NLOGIT in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: NLOGIT is common in secondary-school and first-year university syllabi. It links to neighbouring topics Discontinued software, Econometrics software, Proprietary software, so understanding it makes those chapters shorter.
In everyday life: Look for NLOGIT outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study NLOGIT in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what NLOGIT means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain NLOGIT out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is NLOGIT in simple terms?

Why does NLOGIT matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study NLOGIT?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on NLOGIT.