Ben Goodrich
Datos Biográficos
| ID | 4380050 |
|---|---|
| NOMBRE | Ben Goodrich |
| NOMBRES | Ben |
| APELLIDO | Goodrich |
| FIRMA | BEN GOODRICH |
| AFILIACIONES | Columbia University |
| VERIFICADO | No |
| TOTAL DE OBRAS | 4 |
| TOTAL DE CITAS | 17 |
| TOTAL COMO AUTOR | 4 |
| TOTAL COMO EDITOR | 0 |
| PRIMER AÑO DE PUBLICACIÓN | 2006 |
| AÑO MÁS RECIENTE DE PUBLICACIÓN | 2019 |
| ÍNDICE H | 1 |
R-squared for Bayesian Regression Models
The usual definition of R2 (variance of the predicted values divided by the variance of the data) has a problem for Bayesian fits, as the numerator can be larger than the denominator. We propose an alternative definition similar to one that has appeared in the survival analysis literature: the variance of the predicted values divided by the variance of predicted values plus the expected variance of the errors.
Stan
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood …
Multiple Imputation for Continuous and Categorical Data
We consider the relative performance of two common approaches to multiple imputation (MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a joint MVN distribution; and conditional MI, in which each variable is modeled conditionally on all the others. In order to use the multivariate normal distribution, implementations of joint MVN MI typically assume that categories of discrete variables are probabilistically …
A Comment on ‘Rewarding Impatience’
In Lisa Blaydes's article, "Rewarding Impatience: A Bargaining and Enforcement Model of OPEC," (International Organization, Spring 2004), the oil production of members of the Organization of Petroleum Exporting Countries (OPEC) depends on the extent to which they discount future gains. This comment discusses computer-related errors in the original article and determines how the results change when the errors are rectified. I then add country fixe…
Multiple Imputation for Continuous and Categorical Data
We consider the relative performance of two common approaches to multiple imputation (MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a joint MVN distribution; and conditional MI, in which each variable is modeled conditionally on all the others. In order to use the multivariate normal distribution, implementations of joint MVN MI typically assume that categories of discrete variables are probabilistically …
A Comment on ‘Rewarding Impatience’
In Lisa Blaydes's article, "Rewarding Impatience: A Bargaining and Enforcement Model of OPEC," (International Organization, Spring 2004), the oil production of members of the Organization of Petroleum Exporting Countries (OPEC) depends on the extent to which they discount future gains. This comment discusses computer-related errors in the original article and determines how the results change when the errors are rectified. I then add country fixe…
A Comment on ‘Rewarding Impatience’
In Lisa Blaydes's article, "Rewarding Impatience: A Bargaining and Enforcement Model of OPEC," (International Organization, Spring 2004), the oil production of members of the Organization of Petroleum Exporting Countries (OPEC) depends on the extent to which they discount future gains. This comment discusses computer-related errors in the original article and determines how the results change when the errors are rectified. I then add country fixe…
Multiple Imputation for Continuous and Categorical Data
We consider the relative performance of two common approaches to multiple imputation (MI): joint multivariate normal (MVN) MI, in which the data are modeled as a sample from a joint MVN distribution; and conditional MI, in which each variable is modeled conditionally on all the others. In order to use the multivariate normal distribution, implementations of joint MVN MI typically assume that categories of discrete variables are probabilistically …
Stan
Stan is a probabilistic programming language for specifying statistical models. A Stan program imperatively defines a log probability function over parameters conditioned on specified data and constants. As of version 2.14.0, Stan provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods such as the No-U-Turn sampler, an adaptive form of Hamiltonian Monte Carlo sampling. Penalized maximum likelihood …
R-squared for Bayesian Regression Models
The usual definition of R2 (variance of the predicted values divided by the variance of the data) has a problem for Bayesian fits, as the numerator can be larger than the denominator. We propose an alternative definition similar to one that has appeared in the survival analysis literature: the variance of the predicted values divided by the variance of predicted values plus the expected variance of the errors.
Mathematics (3 obras) · Statistical Methods and Bayesian Inference (3 obras) · Statistics (3 obras) · Bayesian probability (2 obras) · Computer Science (2 obras) · Econometrics (2 obras) · Advanced Causal Inference Techniques (1 obras) · Algorithm (1 obras) · Analysis of variance (1 obras) · Applied Mathematics (1 obras)