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Model estimation:
- all coefficients are estimated simultaneously using maximum likelihood estimation (i.e. ‘full information’ estimates);
- models can be binomial, multinomial, or tree (nested) logit models, with unlimited branches and levels; alternatively, mixed logit or error component analysis, including differing distributions (including exponentials, e.g. lognormal) and correlated error terms;
- non-linear utility functions allow attraction variables to be included correctly;
- composite alternatives can be indicated as chosen;
- coefficient estimates, standard errors, correctly calculated elasticities, consumer surplus measures and several detailed tests are all standard, with informative, clearly labelled, well-laid-out output, suitable for immediate incorporation in reports;
- a function in the ALOGIT can be used to make comparisons between different model variants;
- an option for initial linear estimation reduces run time for complex models;
- problem sizes are not limited by ALOGIT.
ALOGIT has been in intensive use by leading-edge modellers for more than 30 years and has been developed throughout that period to meet the needs of advanced modelling. As a result, ALOGIT has a high level of reliability and numerous features and facilities that are useful for professional modelling. The Help file gives an overview of the possibilities (download zipped version of Help but note that this does not work with the most recent versions of Windows).
ALOGIT估算了通用logit模型的参数。主要的功能有:
树型模型( 嵌套、分层的)与简单的logit模型相比,它支持模型中的替代方法与简单的重新训练方法关联,但仍然保持操作简单和操作快速的特征。
组合logit模型使用灵活的‘error components’规范,它可以使用线性或指数形式,这允许系数中的对数正态扰动。
Only version 4.3 of ALOGIT is available now but send us a mail if you need help with older versions. The points below may help in the first instance.
ALOGIT 3.2 was introduced in July 1992 and we cannot remember much about versions before that (although 3.1 was quite like 3.2).
Forecasting:
- the user can specify detailed scenarios which incorporate a series of changes in the variables influencing choice, and ALOGIT can predict, display and analyse the consequent changes in behaviour;
- a function in the ALOGIT can be used to make graphical and tabular presentations of scenario outputs; alternatively, output can be made to other programs such as Excel.
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