30
Aug

SAS ERROR: Cannot load SSL support. on Microsoft Windows

When using SAS with HTTPS or FTPS, which requires SSL/TLS support, you may see this error message in the SAS log.


ERROR: Cannot load SSL support.

Here is an example of code that can trigger the error.


filename myref url "https://www.google.com";
data _null_;
infile myref;
run;

The cause was that

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For more posts like this, see Heuristic Andrew.

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30
Aug

Analog clocks, vinyl records, and payphones

What do people have in common who have used analog clocks, vinyl records, and payphones?  They were all probably born before 1980! Now, let's focus on those payphones!... A lot of young kids these days can't imagine a world where everyone doesn't have a wireless phone. My buddy Ed likes […]

The post Analog clocks, vinyl records, and payphones appeared first on SAS Learning Post.

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30
Aug

Improve matching results with suggestion based matching in SAS Data Quality

Have you ever had problems matching data that has typographical errors in it? Because of the nature of arbitrary typos and incorrect spelled words a specific matching technique is required to tackle those cases. SAS Data Quality, with its traditional, in nature deterministic matching approach is by nature not best […]

Improve matching results with suggestion based matching in SAS Data Quality was published on SAS Users.

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29
Aug

Observation and Performance Window

The first step of building a predictive model is to define a target variable. For that we need to define the observation and performance window.

Observation Window

It is the period from where independent variables /predictors come from. In other words, the independent variables are created considering this period (window) only.

Performance Window

It is the period from where dependent variable /target come from. It is the period following the observation window.

Example

Suppose you are developing a customer attrition model for retail bank customers. 'Customer attrition' means customers are leaving the bank. You have historical data from Jan'13 to Dec'15. To create independent variables / predictors, data from Jan'13 to May'15 would be used. Customers who attrited during July'15 - Dec'15 are considered as attritors (or events) in the model. One month lag between observation and performance window would be used as a period during which the population will be scored when implementing the model.
Observation and Performance Window

Factors in choosing Observation Window

1. Take into enough cases to develop a model.
2. Take into account any seasonal influences.
3. No fixed window for all the models. Depends on the type of model.


Factors in choosing Performance Window
1. Performance window depends on the model you are building. In other words, it depends on the definition of product. For example, performance window for customer attrition for savings product model would be different than performance window for Certificate of Deposit model.

2. Initially take multiple length of the performance windows and calculate event rate against these periods. Select the period at which event rate stabilizes.


Rolling Performance Window
It implies taking multiple windows to build a model but the duration of performance window is fixed as shown in the image below.
Rolling Performance Window

Why Rolling Performance Window

1. Seasonality

It is not always a case that the behavior of attributes of customers are constant. For example, the attrition rate of a particular period is 10%. In the other period, it may go up or down. There could be some seasonality related to it. When we take a single performance window, we assume that the variables are constant over time. When we take multiple performance window, we capture seasonality in the model.

2. Including Multiple Campaigns

If you are building a campaign response model, campaign data of multiple periods should be considered.

Example : Campaign Response - Rolling Performance Windows
  1. Customers targeted in Jan 2015 for the home loan campaign–whether the customers have taken the loan from Feb 2015 to April 2015
  2. Customers targeted in Feb 2015 for the home loan campaign–whether the customers have taken the loan converted from March 2015 to May 2015
  3. Customers targeted in March 2015 for the home loan campaign–whether the customers have taken the loan from April 2015 to June 2015
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29
Aug

Present at SAS Global Forum 2017 – Call for content now open

SAS Global Forum is the premier event for SAS users to learn, teach, and network with each other and SAS experts. SAS Global Forum 2017 takes place April 2-5 in Orlando, Florida, where you can join more than 5,000 SAS users from nearly every country imaginable. Although SAS Global Forum […]

Present at SAS Global Forum 2017 – Call for content now open was published on SAS Users.

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29
Aug

You can write SAS programs using Dragon

One of my concerns not being able to use my left hand has been how I’m going to be able to continue coding. As my job entails a lot of coding, this has been a major worry. While I have yet to figure out how to use Dragon for JavaScript – I’m not sure at […] Read More
29
Aug

Weighted percentiles

Many univariate descriptive statistics are intuitive. However, weighted statistic are less intuitive. A weight variable changes the computation of a statistic by giving more weight to some observations than to others. This article shows how to compute and visualize weighted percentiles, also known as a weighted quantiles, as computed by […]

The post Weighted percentiles appeared first on The DO Loop.

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28
Aug

Clinical Graphs - Risk Difference Plots

Often I have written articles that are motivated by some question by a user on how to create a particular graph, or how to work around some shortcoming in the feature set to create the graph you need.  This time, I got a question about Clinical Graphs that were mostly working […]

The post Clinical Graphs - Risk Difference Plots appeared first on Graphically Speaking.

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27
Aug

SAS Statistical Business Analyst Certification Questions and Answers

This article covers some of the SAS Certified Statistical Business Analyst certification questions with detailed answers. This certification covers some of the most widely used statistical techniques such as ANOVA, linear and logistic regression.To cra... Read More
26
Aug

MWSUG preview: When ANY Function will just NOT do!

When I attended my first SAS conference in 2003 I was not only a first-timer, I was a first time presenter.  Needless to say I was a bit nervous.  I did not know what to expect.  Was my topic good enough for these savvy programmers and statisticians?  Well my first […]

MWSUG preview: When ANY Function will just NOT do! was published on SAS Users.

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