One of the earliest examples of simulation-based model checking in statistics comes from the 1954 book by Robert Bush and Frederick Mosteller, Stochastic Models for Learning. They fit a probability model to data on dogs being shocked in a research lab (yeah, I know, not an experiment that would be done today). Then they simulate […]
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Academics / Mathematics : Statistical Modeling, Causal Inference, and Social Science

What better way to start then new year than with some hard-core statistical theory? Ryan Martin and Chuanhai Liu send along a new paper on inferential models: Probability is a useful tool for describing uncertainty, so it is natural...

Academics / Mathematics : Statistical Modeling, Causal Inference, and Social Science

This is one of my favorite papers: In applications, statistical models are often restricted to what produces reasonable estimates based on the data at hand. In many cases, however, the principles that allow a model to be restricted ...

Academics / Mathematics : Statistical Modeling, Causal Inference, and Social Science

We have lots of models for overdispersed count data but we rarely see underdispersed data. But now I know what example I’ll be giving when this next comes up in class. From a book review by Theo Tait: A number of shark species go in...

Academics / Mathematics : Statistical Modeling, Causal Inference, and Social Science

Data analysis recipes: Fitting a model to data: We go through the many considerations involved in fitting a model to data, using as an example the fit of a straight line to a set of points in a two-dimensional plane. Standard weight...

Academics : The Endeavour

If you train a model on a set of data, it should fit that data well. The hope, however, is that it will fit a new set of data well. So in machine learning and statistics, people split their data into two parts. They train the model ...

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