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Site relaunches with improved content, organization and navigation. In 2016, a cross-divisional SAS team created developer.sas.com. Their mission: Build a bridge between SAS (and our software) and open source developers. The initial effort made available basic information about SAS® Viya® and integration with open source technologies. In June 2018, the
If you don't have a SAS/Graph license, then you're probably using the ODS Graphics 'sg' procedures that come with Base SAS to create your graphs and maps. And if you've tried plotting data on a map, you probably noticed that SGmap lets you overlay point-data on an OpenStreetmap, but you
Longitudinal data are used in many health-related studies in which individuals are measured at multiple points in time to monitor changes in a response variable, such as weight, cholesterol, or blood pressure. There are many excellent articles and books that describe the advantages of a mixed model for analyzing longitudinal
In just over six months, football fans across Europe face a logistical maze: how to follow their favourite teams from stadium to stadium as games are played all over the continent. We described the challenge and optimisation approach we took in a separate piece. In this gallery, we walk
Football fans around the world have something exciting to look forward to, with the European Championship scheduled to take place in June and July 2020. Twenty teams out of 24 have already qualified for the tournament, and after last Saturday's draw, the teams and fans are now getting ready to
The Local Government Association has concluded that in the last 10 years, there has been a reduction in funding of 60p for every £1.
With time series data analysis, we can apply moving average methods to predict data points without seasonality. This includes Simple Average (SA), Simple Moving Average (SMA), Weighted Moving Average (WMA), Exponential Moving Average (EMA), etc. For series with a trend but without seasonality, we can use linear, non-linear and autoregressive
This article discusses how to restrict a multivariate function to a linear subspace. This is a useful technique in many situations, including visualizing an objective function that is constrained by linear equalities. For example, the graph to the right is from a previous article about how to evaluate quadratic polynomials.
If you are a caregiver, the holiday season may bring less Peace and Good Tidings, and more Stress and Frustration. If you are already feeling overwhelmed with caregiving responsibilities, the holidays may feel more of a burden than a joy. I think it is fair to say that the holidays are
North Carolina recently re-drew the congressional district boundaries for the upcoming 2020 election. Here's a copy of the new map, from the ncleg.gov website: A couple of years ago, I created an enhanced version of the 2016/18 map, and I thought I'd do the same for the new 2020 map...
A business glossary improves data quality – one of the top five ways it makes analytics better.
I grew up in Massachusetts. Waking up to a fresh blanket of snow was not unusual on Thanksgiving. I remember the windows on our small, ranch home were often frosty with condensation in the morning. Mom would take a hand towel to wipe them down. The house was heated with
Los datos, y sobre todo su significado y usabilidad, se han ido transformando con el tiempo. Anteriormente hablar de datos era pensar en unos y ceros, en tablas estáticas o incluso en materiales que no se aprovechaban. Hoy, pensar en datos es pensar en la fuente principal de las historias,
The SAS Global Certification Program started in 1999 and has issued over 150,000 credentials to SAS users. Today, the program offers 23 different credentials across seven categories.
What is an efficient way to evaluate a multivariate quadratic polynomial in p variables? The answer is to use matrix computations! A multivariate quadratic polynomial can be written as the sum of a purely quadratic term (degree 2), a purely linear term (degree 1), and a constant term (degree 0).