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In statistics, a tobit model is any of a class of regression models in which the observed range of the dependent variable is censored in some way. The term was coined by Arthur Goldberger in reference to James Tobin, who developed the model in 1958 to mitigate the problem of zero-inflated data for observations of household expenditure on durable goods.…
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Explore the main themes, entities and connections around Tobit model. Start with the topic map, then use the sections below for research and deeper semantic analysis.
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tobit model type models likelihood displaystyle variable censored function regression data latent dependent observed zero ii isbn truncated probability tobin's
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Tobit model | is a | special case of a censored regression model | 0.90 | text |
| Tobit model | has application | Tobit | 0.60 | section |
| Tobit model | has application | In | 0.60 | section |
| Tobit model | has application | For | 0.60 | section |
| Tobit model | has application | Dahlberg | 0.60 | section |
| Tobit model | has application | Johansson | 0.60 | section |
| Tobit model | has application | Dubois | 0.60 | section |
| Tobit model | has application | Fattore | 0.60 | section |
| Tobit model | has application | European Union | 0.60 | section |
| Tobit model | has application | Polish | 0.60 | section |
| Tobit model | has application | The | 0.60 | section |
| Tobit model | has application | Both | 0.60 | section |
These clusters group vocabulary that occurs around closely connected concepts in the source material.
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