The DO Loop

Analytics

Find out how analytics, from data mining to cognitive computing, is changing the way we do business

Rick WicklinOctober 12, 2020 1

Visualize uncertainty in regression predictions

You've probably seen many graphs that are similar to the one at the right. This plot shows a regression line overlaid on a scatter plot of some data. Given a value for the independent variable (x), the regression line gives the best prediction for the mean of the response variable

English

Analytics | Programming Tips

Rick WicklinOctober 7, 2020 0

The Poisson-binomial distribution for hundreds of parameters

A previous article shows how to use a recursive formula to compute exact probabilities for the Poisson-binomial distribution. The recursive formula is an O(N2) computation, where N is the number of parameters for the Poisson-binomial (PB) distribution. If you have a distribution that has hundreds (or even thousands) of parameters,

English

Analytics | Programming Tips

Rick WicklinSeptember 28, 2020 0

The Poisson-binomial distribution

The Poisson-binomial distribution is a generalization of the binomial distribution. For the binomial distribution, you carry out N independent and identical Bernoulli trials. Each trial has a probability, p, of success. The total number of successes, which can be between 0 and N, is a binomial random variable. The distribution

English

Analytics | Learn SAS

Rick WicklinSeptember 21, 2020 0

Regression with inequality constraints on parameters

A previous article discussed how to solve regression problems in which the parameters are constrained to be a specified constant (such as B1 = 1) or are restricted to obey a linear equation such as B4 = –2*B2. In SAS, you can use the RESTRICT statement in PROC REG to

English

Analytics | Programming Tips

Rick WicklinSeptember 16, 2020 1

Restricted least squares regression in SAS

A data analyst recently asked a question about restricted least square regression in SAS. Recall that a restricted regression puts linear constraints on the coefficients in the model. Examples include forcing a coefficient to be 1 or forcing two coefficients to equal each other. Each of these problems can be

English

Analytics | Programming Tips

Rick WicklinSeptember 10, 2020 0

Iterative proportional fitting in SAS

I previously wrote about the RAS algorithm, which is a simple algorithm that performs matrix balancing. Matrix balancing refers to adjusting the cells of a frequency table to match known values of the row and column sums. Ideally, the balanced matrix will reflect the structural relationships in the original matrix.

English

Analytics | Programming Tips

Rick WicklinSeptember 8, 2020 1

Matrix balancing: Update matrix cells to match row and column sums

Matrix balancing is an interesting problem that has a long history. Matrix balancing refers to adjusting the cells of a frequency table to match known values of the row and column sums. One of the early algorithms for matrix balancing is known as the RAS algorithm, but it is also

English

Analytics | Data Visualization | Learn SAS

Rick WicklinJuly 1, 2020 4

Pooled, within-group, and between-group covariance matrices

A previous article discusses the pooled variance for two or groups of univariate data. The pooled variance is often used during a t test of two independent samples. For multivariate data, the analogous concept is the pooled covariance matrix, which is an average of the sample covariance matrices of the

English

Analytics | Programming Tips

Rick WicklinJune 24, 2020 2

The Kolmogorov D distribution and exact critical values

If you have ever run a Kolmogorov-Smirnov test for normality, you have encountered the Kolmogorov D statistic. The Kolmogorov D statistic is used to assess whether a random sample was drawn from a specified distribution. Although it is frequently used to test for normality, the statistic is "distribution free" in

English

Analytics

Rick WicklinJune 8, 2020 0

Interactions with spline effects in regression models

A SAS customer asked how to specify interaction effects between a classification variable and a spline effect in a SAS regression procedure. There are at least two ways to do this. If the SAS procedure supports the EFFECT statement, you can build the interaction term in the MODEL statement. For

English

Blogs

Blogs

Analytics