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Geographically Weighted Bivariate Probit Ordinal Regression

https://doi.org/10.2139/ssrn.6320078

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Use and interpretation of spatial autoregressive probit models

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Analysis of Prevalence of Malaria and Anemia Using Bivariate Probit Model

inferredcites →https://doi.org/10.1016/j.asieco.2010.03.009openalex-snapshot

Bivariate probit analysis of differences between male and female formal employment in urban China

inferredcites →https://doi.org/10.1016/j.jtrangeo.2005.11.002openalex-snapshot

Exploring contextual variations in land use and transport analysis using a probit model with geographical weights

inferredcites →https://doi.org/10.1016/j.mex.2024.102903openalex-snapshot

Spatial clustering based on geographically weighted multivariate generalized gamma regression

inferredcites →https://doi.org/10.1016/j.mex.2025.103192openalex-snapshot

Industrial wastewater treatment and reuse: Heckman probit sample selection model

inferredcites →https://doi.org/10.1080/17457300.2024.2349554openalex-snapshot

Bivariate ordered probit modelling of motorcycle riders and pillion passengers’ injury severities relationship and associated risk factors

inferredcites →https://doi.org/10.1111/j.1467-9787.1992.tb00190.xopenalex-snapshot

PROBIT WITH SPATIAL AUTOCORRELATION

inferredcites →https://doi.org/10.1177/1536867x0400400206openalex-snapshot

Computing Interaction Effects and Standard Errors in Logit and Probit Models

inferredcites →https://doi.org/10.2307/2986327openalex-snapshot

A Bivariate Ordered Probit Model with Truncation: Helmet Use and Motorcycle Injuries

inferredcites →https://doi.org/10.3390/math11030579openalex-snapshot

Parameter Estimation and Hypothesis Testing of The Bivariate Polynomial Ordinal Logistic Regression Model

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