Showing 7 of total 7 results (show query)
jhelvy
logitr:Logit Models w/Preference & WTP Space Utility Parameterizations
Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. Weighted models can also be estimated. An option is available to run a parallelized multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for predicting expected choices and choice probabilities for sets of alternatives based on an estimated model. Mixed logit models can include uncorrelated or correlated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) <doi:10.1017/CBO9780511805271>. More details can be found in Helveston (2023) <doi:10.18637/jss.v105.i10>.
Maintained by John Helveston. Last updated 5 months ago.
log-likelihoodlogitlogit-modelmixed-logitmlogitmultinomial-regressionmxlmxl-modelspreference-spacepreferenceswillingness-to-paywtp
38.5 match 54 stars 9.10 score 119 scripts 1 dependents
shivaway
IAPWS95:Thermophysical Properties of Water and Steam
Functions for Water and Steam Properties based on the International Association for the Properties of Water (IAPWS) Formulation 1995 for the Thermodynamic Properties of Ordinary Water Substance for General and Scientific Use and on the releases for viscosity, conductivity, surface tension and melting pressure.
Maintained by Shawn Way. Last updated 2 years ago.
3.3 match 4.76 score 116 scripts
cran
DCchoice:Analyzing Dichotomous Choice Contingent Valuation Data
Functions for analyzing dichotomous choice contingent valuation (CV) data. It provides functions for estimating parametric and nonparametric models for single-, one-and-one-half-, and double-bounded CV data. For details, see Aizaki et al. (2022) <doi:10.1007/s42081-022-00171-1>.
Maintained by Hideo Aizaki. Last updated 2 years ago.
6.9 match 1 stars 2.18 score 31 scripts 1 dependentscran
DCEmgmt:DCE Data Reshaping and Processing
Prepare the results of a DCE to be analysed through choice models.'DCEmgmt' reshapes DCE data from wide to long format considering the special characteristics of a DCE. 'DCEmgmt' includes the function 'DCEestm' which estimates choice models once the database has been reshaped with 'DCEmgmt'.
Maintained by Daniel Perez-Troncoso. Last updated 3 years ago.
6.4 match 2.00 score
mauricio1986
gmnl:Multinomial Logit Models with Random Parameters
An implementation of maximum simulated likelihood method for the estimation of multinomial logit models with random coefficients as presented by Sarrias and Daziano (2017) <doi:10.18637/jss.v079.i02>. Specifically, it allows estimating models with continuous heterogeneity such as the mixed multinomial logit and the generalized multinomial logit. It also allows estimating models with discrete heterogeneity such as the latent class and the mixed-mixed multinomial logit model.
Maintained by Mauricio Sarrias. Last updated 3 years ago.
2.3 match 4 stars 4.27 score 51 scriptscran
RcmdrPlugin.DCCV:R Commander Plug-in for Dichotomous Choice Contingent Valuation
Adds menu items to the R Commander for parametric analysis of dichotomous choice contingent valuation (DCCV) data. CV is a question-based survey method to elicit individuals' preferences for goods and services. This package depends on functions regarding parametric DCCV analysis in the package DCchoice. See Carson and Hanemann (2005) <doi:10.1016/S1574-0099(05)02017-6> for DCCV.
Maintained by Hideo Aizaki. Last updated 10 months ago.
1.9 match 1 stars 1.30 score
vsimko
rroad:Road Condition Analysis
Computation of the International Roughness Index (IRI) given a longitudinal road profile. The IRI can be calculated for a single road segment or for a sequence of segments with a fixed length (e. g. 100m). For the latter, an overlap of the segments can be selected. The IRI and likewise the algorithms for its determination are defined in Sayers, Michael W; Gillespie, Thomas D; Queiroz, Cesar A.V. 1986. The International Road Roughness Experiment (IRRE) : establishing correlation and a calibration standard for measurements. World Bank technical paper; no. WTP 45. Washington, DC : The World Bank. (ISBN 0-8213-0589-1) available from <http://documents.worldbank.org/curated/en/326081468740204115>.
Maintained by Viliam Simko. Last updated 5 years ago.
carindexirimonitoringroad-conditionroad-safetyroad-trafficroadsroads-and-highwaysroughness
0.5 match 13 stars 4.11 score 7 scripts