What is a spaghetti plot? Spaghetti plots are line plots that involve many overlapping lines. Like spaghetti on your plate, they can be hard to unravel, yet for many analysts they are a delicious staple of data visualization. This article presents the good, the bad, and the messy about spaghetti
Tag: Time series
Last week I showed how to use PROC EXPAND to compute moving averages and other rolling statistics in SAS. Unfortunately, PROC EXPAND is part of SAS/ETS software and not every SAS site has a license for SAS/ETS. For simple moving averages, you can write a DATA step program, as discussed
A common question on SAS discussion forums is how to compute a moving average in SAS. This article shows how to use PROC EXPAND and contains links to articles that use the DATA step or macros to compute moving averages in SAS. In a previous post, I explained how to
A moving average (also called a rolling average) is a statistical technique that is used to smooth a time series. Moving averages are used in finance, economics, and quality control. You can overlay a moving average curve on a time series to visualize how each value compares to a rolling
In SAS, the aspect ratio of a graph is the physical height of the graph divided by the physical width. Recently I demonstrated how to set the aspect ratio of graphs in SAS by using the ASPECT= option in PROC SGPLOT or by using the OVERLAYEQUATED statement in the Graph
You've probably heard of a random walk, but have you heard about the drunkard's walk? I've previously written about how to simulate a one-dimensional random walk in SAS. In the random walk, you imagine a person who takes a series of steps where the step size and direction is a
I recently wrote about how to overlay multiple curves on a single graph by reshaping wide data (with many variables) into long data (with a grouping variable). The implementation used PROC TRANSPOSE, which is a procedure in Base SAS. When you program in the SAS/IML language, you might encounter data
Data. To a statistician, data are the observed values. To a SAS programmer, analyzing data requires knowledge of the values and how the data are arranged in a data set. Sometimes the data are in a "wide form" in which there are many variables. However, to perform a certain analysis
Vector languages such as SAS/IML, MATLAB, and R are powerful because they enable you to use high-level matrix operations (matrix multiplication, dot products, etc) rather than loops that perform scalar operations. In general, vectorized programs are more efficient (and therefore run faster) than programs that contain loops. For an example
Finding the maximum value of a function is an important task in statistics. There are three approaches to finding a maxima: When the function is available as an analytic expression, you can use an optimization algorithm to find the maxima. For example, in the SAS/IML language, you can use any