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StataNow puts new features at your fingertips as soon as they are ready. With the latest update, you can use H2O machine learning for gradient boosting machine and random forest. Tune hyperparameters, use validation or cross-validation, explain predictions, and more.
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Bayesian model averaging (BMA)
Causal mediation analysis
Tables of descriptive statistics
Group sequential designs
Robust inference for linear models
Wild cluster bootstrap
Flexible demand systems
TVCs with interval-censored Cox model
GOF plots for survival models
Lasso for Cox model
Heterogeneous DID
Multilevel meta-analysis
Meta-analysis for prevalence
Local projections for IRFs
Model selection for ARIMA and ARFIMA
RERI
New spline functions
Corrected and consistent AICs
IV fractional probit model
IV quantile regression
All-new graph style
Graph colors by variable
Alias variables across frames
Frame sets
Boost-based regular expressions
Vectorized numerical integration
New reporting features
Do-file Editor enhancements
Data Editor enhancements
More
Bayesian model averaging (BMA)
Causal mediation analysis
Tables of descriptive statistics
Group sequential designs
Robust inference for linear models
Wild cluster bootstrap
Flexible demand systems
TVCs with interval-censored Cox model
Lasso for Cox model
GOF plots for survival models
RERI
New spline functions
Corrected and consistent AICs
IV fractional probit model
IV quantile regression
Heterogeneous DID
Multilevel meta-analysis
Meta-analysis for prevalence
Local projections for IRFs
Model selection for ARIMA and ARFIMA
Alias variables across frames
Frame sets
Boost-based regular expressions
Vectorized numerical integration
Data Editor enhancements
Do-file Editor enhancements
New reporting features
Graph colors by variable
All-new graph style
More
Bayesian model averaging (BMA)
Causal mediation analysis
Tables of descriptive statistics
Heterogeneous DID
Group sequential designs
Multilevel meta-analysis
Meta-analysis for prevalence
Robust inference for linear models
Wild cluster bootstrap
Local projections for IRFs
Model selection for ARIMA and ARFIMA
Flexible demand systems
TVCs with interval-censored Cox model
Lasso for Cox model
GOF plots for survival models
RERI
IV quantile regression
IV fractional probit model
Corrected and consistent AICs
New spline functions
Alias variables across frames
Frame sets
Boost-based regular expressions
Vectorized numerical integration
New reporting features
Do-file Editor enhancements
Data Editor enhancements
Graph colors by variable
All-new graph style
More
Machine learning via H2O:
Ensemble decision treesLatest
High-dimensional fixed effects (HDFE)
Bayesian variable selection for linear model
Interval-censored multiple-event Cox model
Bayesian quantile regression
Panel-data VAR model
Correlated random-effects (CRE) model
Control-function linear and probit models
SVAR models via instrumental variables
IV local-projection IRFs
Bayesian asymmetric Laplace model
Inference robust to weak instruments
Meta-analysis for correlations
Mundlak specification test
Do-file Editor: Autocompletion, templates, and more
Colors by variable for more graphs
More
Machine learning via H2O:
Ensemble decision treesLatest
High-dimensional fixed effects (HDFE)
Bayesian variable selection for linear model
Interval-censored multiple-event Cox model
Meta-analysis for correlations
Bayesian quantile regression
Panel-data VAR model
Inference robust to weak instruments
Mundlak specification test
Correlated random-effects (CRE) model
Control-function linear and probit models
SVAR models via instrumental variables
IV local-projection IRFs
Bayesian asymmetric Laplace model
Colors by variable for more graphs
Do-file Editor: Autocompletion, templates, and more
More
Machine learning via H2O:
Ensemble decision treesLatest
High-dimensional fixed effects (HDFE)
Bayesian variable selection for linear model
Interval-censored multiple-event Cox model
Meta-analysis for correlations
Correlated random-effects (CRE) model
Control-function linear and probit models
Bayesian quantile regression
Bayesian asymmetric Laplace model
Panel-data VAR model
Inference robust to weak instruments
SVAR models via instrumental variables
IV local-projection IRFs
Mundlak specification test
Do-file Editor: Autocompletion, templates, and more
Colors by variable for more graphs
More
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15 May · Bangkok
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