This post is the third one of our series on the history and foundations of econometric and machine learning models. Part 2 is online here. Exponential family and linear models The Gaussian linear model is a special case of a large family of linear models, obtained when the conditional distribution of [latex]Y[/latex] (given the covariates) belongs to the exponential family[latex display="true"] f(y_i|\theta_i,\phi)=\exp\left(\frac{y_i\theta_i-b(\theta_i)}{a(\phi)}+c(y_i,\phi)\right) [/latex] ..
This chapter of the Handbook of Computational Economics is mostly about research on active learning ...
We consider ergodic diffusion processes for which the class of invariant measures is an exponential ...
This chapter of the Handbook of Computational Economics is mostly about research on active learning ...
This post is the sixth one of our series on the history and foundations of econometric and machine l...
This text is for a one semester graduate course in statistical theory and covers minimal and comple...
This post is the nineth (and probably last) one of our series on the history and foundations of econ...
This post is the seventh one of our series on the history and foundations of econometric and machine...
In a series of posts, I wanted to get into details of the history and foundations of econometric and...
This dissertation considers the problem of learning the underlying statistical structure of complex ...
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear reg...
This is not a copy of the original, which is in the University of Washington library because the or...
The dissertation consists of three independent essays, and they are put in as three chapters. The go...
This is a companion volume to Plane Answers to Complex Questions: The Theory 0/ Linear Models. It co...
We consider natural and general exponential families Qmm∈M on ℜd parametrized by the means...
In many families of distributions, maximum likelihood estimation is intractable because the normaliz...
This chapter of the Handbook of Computational Economics is mostly about research on active learning ...
We consider ergodic diffusion processes for which the class of invariant measures is an exponential ...
This chapter of the Handbook of Computational Economics is mostly about research on active learning ...
This post is the sixth one of our series on the history and foundations of econometric and machine l...
This text is for a one semester graduate course in statistical theory and covers minimal and comple...
This post is the nineth (and probably last) one of our series on the history and foundations of econ...
This post is the seventh one of our series on the history and foundations of econometric and machine...
In a series of posts, I wanted to get into details of the history and foundations of econometric and...
This dissertation considers the problem of learning the underlying statistical structure of complex ...
Here we present a nearly complete treatment of the Grand Universe of linear and weakly nonlinear reg...
This is not a copy of the original, which is in the University of Washington library because the or...
The dissertation consists of three independent essays, and they are put in as three chapters. The go...
This is a companion volume to Plane Answers to Complex Questions: The Theory 0/ Linear Models. It co...
We consider natural and general exponential families Qmm∈M on ℜd parametrized by the means...
In many families of distributions, maximum likelihood estimation is intractable because the normaliz...
This chapter of the Handbook of Computational Economics is mostly about research on active learning ...
We consider ergodic diffusion processes for which the class of invariant measures is an exponential ...
This chapter of the Handbook of Computational Economics is mostly about research on active learning ...