The DO Loop

Analytics

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

Analytics | Learn SAS

Rick WicklinMarch 24, 2021 3

An overview of regression diagnostic plots in SAS

When you fit a regression model, it is useful to check diagnostic plots to assess the quality of the fit. SAS, like most statistical software, makes it easy to generate regression diagnostics plots. Most SAS regression procedures support the PLOTS= option, which you can use to generate a panel of

English

Analytics

Rick WicklinMarch 17, 2021 1

The Farey sequence

Here is an interesting math question: How many reduced fractions in the interval (0, 1) have a denominator less than 100? The question is difficult is because of the word "reduced." If we only care about the total number of fractions in (0,1) whose denominator is less than 100, we

English

Analytics | Programming Tips

Rick WicklinMarch 15, 2021 2

The generalized gamma distribution

A SAS customer wanted to compute the cumulative distribution function (CDF) of the generalized gamma distribution. For any continuous distribution, the CDF is the integral of the probability density function (PDF), which usually has an explicit formula. Accordingly, he wanted to compute the CDF by using the QUAD function in

English

Analytics | Data Visualization | Learn SAS

Rick WicklinMarch 8, 2021 0

The conditional distribution of a response variable

I recently learned about a new feature in PROC QUANTREG that was added in SAS/STAT 15.1 (part of SAS 9.4M6). Recall that PROC QUANTREG enables you to perform quantile regression in SAS. (If you are not familiar with quantile regression, see an earlier article that describes quantile regression and provides

English

Analytics

Rick WicklinFebruary 8, 2021 0

A matrix is singular if its rows are arithmetic sequences

Look at the following matrices. Do you notice anything that these matrices have in common? If you noticed that the rows of each matrix are arithmetic progressions, good for you. For each row, there is a constant difference (also called the "increment") between adjacent elements. For these examples: In the

English

Analytics | Programming Tips

Rick WicklinFebruary 3, 2021 2

Generate random points on a sphere

In a previous article, I showed how to generate random points uniformly inside a d-dimensional sphere. In that article, I stated the following fact: If Y is drawn from the uncorrelated multivariate normal distribution, then S = Y / ||Y|| has the uniform distribution on the unit sphere. I was

English

Analytics | Programming Tips

Rick WicklinJanuary 27, 2021 0

The inverse gamma distribution in SAS

The inverse gamma distribution is a continuous probability distribution that is used in Bayesian analysis and in some statistical models. The inverse gamma distribution is closely related to the gamma distribution. For any probability distribution, it is essential to know how to compute four functions: the PDF function, which returns

English

Analytics | Programming Tips

Rick WicklinJanuary 20, 2021 4

The stationary block bootstrap in SAS

This is the third and last introductory article about how to bootstrap time series in SAS. In the first article, I presented the simple block bootstrap and discussed why bootstrapping a time series is more complicated than for regression models that assume independent errors. Briefly, when you perform residual resampling

English

Analytics | Learn SAS | Programming Tips

Rick WicklinJanuary 13, 2021 3

The moving block bootstrap for time series

As I discussed in a previous article, the simple block bootstrap is a way to perform a bootstrap analysis on a time series. The first step is to decompose the series into additive components: Y = Predicted + Residuals. You then choose a block length (L) that divides the total

English

Analytics | Learn SAS | Programming Tips

Rick WicklinJanuary 6, 2021 3

The simple block bootstrap for time series in SAS

For ordinary least squares (OLS) regression, you can use a basic bootstrap of the residuals (called residual resampling) to perform a bootstrap analysis of the parameter estimates. This is possible because an assumption of OLS regression is that the residuals are independent. Therefore, you can reshuffle the residuals to get

English

Blogs

Blogs

Analytics