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Rick WicklinOctober 27, 2021 13

Interpret estimates for a Weibull regression model in SAS

It can be frustrating when the same probability distribution has two different parameterizations, but such is the life of a statistical programmer. I previously wrote an article about the gamma distribution, which has two common parameterizations: one that uses a scale parameter (β) and another that uses a rate parameter

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Analytics | Learn SAS

Rick WicklinOctober 20, 2021 0

An introduction to genetic algorithms in SAS

A genetic algorithm (GA) is a heuristic optimization technique. The method tries to mimic natural selection and evolution by starting with a population of random candidates. Candidates are evaluated for "fitness" by plugging them into the objective function. The characteristics of the better candidates are combined to create a new

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Analytics | Programming Tips

Rick WicklinOctober 18, 2021 2

Crossover and mutation: An introduction to two operations in genetic algorithms

This article uses an example to introduce to genetic algorithms (GAs) for optimization. It discusses two operators (mutation and crossover) that are important in implementing a genetic algorithm. It discusses choices that you must make when you implement these operations. Some programmers love using genetic algorithms. Genetic algorithms are heuristic

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Analytics | Programming Tips

Rick WicklinOctober 13, 2021 1

Penalties versus constraints in optimization problems

Sometimes we can learn as much from our mistakes as we do from our successes. Recently, I needed to solve an optimization problem for which the solution vector was a binary vector subject to a constraint. I was in a hurry. Without thinking much about what I was doing, I

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Analytics | Learn SAS

Rick WicklinOctober 4, 2021 2

Choose samples with specified statistical properties

A reader asked whether it is possible to find a bootstrap sample that has some desirable properties. I am using the term "bootstrap sample" to refer to the result of randomly resampling with replacement from a data set. Specifically, he wanted to find a bootstrap sample that has a specific

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Analytics | Learn SAS | Programming Tips

Rick WicklinSeptember 22, 2021 0

Use simulations to evaluate the accuracy of asymptotic results

The field of probability and statistics is full of asymptotic results. The Law of Large Numbers and the Central Limit Theorem are two famous examples. An asymptotic result can be both a blessing and a curse. For example, consider a result that says that the distribution of some statistic converges

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Analytics | Learn SAS | Programming Tips

Rick WicklinSeptember 15, 2021 1

The partition problem: An optimization approach

I previously wrote about one way to solve the partition problem in SAS. In the partition problem, you divide (or partition) a set of N items into two groups of size k and N-k such that the sum of the items' weights is the same in each group. For example,

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Analytics | Learn SAS | Programming Tips

Rick WicklinSeptember 13, 2021 8

The partition problem

The partition problem has many variations, but recently I encountered it as an interactive puzzle on a computer. (Try a similar game yourself!) The player is presented with an old-fashioned pan-balance scale and a set of objects of different weights. The challenge is to divide (or partition) the objects into

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Analytics | Data Visualization | Learn SAS

Rick WicklinSeptember 9, 2021 0

Simulate proportions for groups

A statistical programmer asked how to simulate event-trials data for groups. The subjects in each group have a different probability of experiencing the event. This article describes one way to simulate this scenario. The simulation is similar to simulating from a mixture distribution. This article also shows three different ways

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Analytics | Programming Tips

Rick WicklinSeptember 1, 2021 1

On the number of bootstrap samples

The number of possible bootstrap samples for a sample of size N is big. Really big. Recall that the bootstrap method is a powerful way to analyze the variation in a statistic. To implement the standard bootstrap method, you generate B random bootstrap samples. A bootstrap sample is a sample

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