Creating an AI Assistant for SAS Viya in 5 steps (@sassoftware/viya-assistantjs) - Part I
Recent Library Articles
Recently in the SAS Community Library: SAS' @kumardeva debunks the myth that developing AI assistants is too hard. He shows you how to use the @sassoftware/viya-assistantjs library to jump start your development.
I have a data file describing users (ID), time periode a service is in use (FromYrMon-ToYrMon) and hours of services (hours). There are two problems. First, the time periods partly overlap. There are also some gaps between the time periods but that is probably correct. Second, the hours of services are not consistently coded in the sense that the same time period (or parts of it) may have differences in hours. The file I want, includes for each ID, one observation per month, the maximum of hours for that month and 0 for months where there are gaps between time periods. I guess the solution will be something like 1) transposing, 2) fill in gaps and 3) pick the highest number of hours for each month.
data have;
input ID FromYrMon YYMMN6 ToYrMon YYMMN6. Hours comma4.2;
datalines;
1 201701 201711 0.75
1 201704 201711 1.20 1 201801 201802 4.00 2 201710 201802 2.00 ; Data want; ID YYMon Hours 1 201701 0.75 1 201702 0.75 1 201703 0.75 1 201704 1.20 1 201705 1.20 1 201706 1.20 1 201707 1.20 1 201708 1.20 1 201709 1.20 1 201710 1.20 1 201711 1.20 1 201712 0.00 (NB) 1 201801 4.00 1 201802 4.00 2 201701 0.00 2 201702 0.00 2 201703 0.00 2 201704 0.00 2 201705 0.00 2 201706 0.00 2 201707 0.00 2 201708 0.00 2 201709 0.00 2 201710 2.00 2 201711 2.00 2 201712 2.00 2 201801 2.00 2 201802 2.00
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Feedback option in proc sql statement we use to display columns in logs. so what is use of it?There is any benefit to see columns in log files.
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Hi, How can I obtain the p-value of the ADF test, which uses AIC or BIC to determine the lag for residuals, in order to test the stationarity of the residuals of a linear regression model? I have tried proc arima but don’t know how to set the AIC/BIC option for lag length. The input data and my code: data df;
input month dep ind1 ind2 ind3;
cards;
1 -4.66344 0.5337595 1.533904 -0.1824561
2 -4.27203 0.5371667 1.638746 -0.2840759
3 -4.31303 0.5187737 1.708084 -0.208212
4 -3.46126 0.501581 1.773411 0.7434088
5 -3.10906 0.5024615 -0.7010086 0.4447428
6 -2.83321 0.50575 0.7289928 0.2619768
7 -2.74544 0.4943883 0.7419567 0.7679318
8 -3.30505 0.4825768 0.7544792 0.273685
9 -3.28185 0.468799 0.9924411 -0.1544852
10 -3.54578 0.4705212 1.133435 0.6179188
;
run;
proc reg
data=df;
model dep = ind1 ind2 ind3 ;
OUTPUT OUT=model_output_c predicted= pred residual=resid;
run;
proc arima data=model_output_c;
identify var=resid STATIONARITY=(ADF) ;
run;
Thank you!
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Welcome to the Nordic FANS AML Network meeting
If you are a SAS user/customer working with AML, you are welcome to join us for this FANS Network meeting about AML (Anti-Money Laundering).
Date: 21/6-2024
Time: 9:00-12:00 CET (light breakfast from 8.30 and Lunch after the Network meeting)
Type: Hybrid (only for SAS AML customers/prospects) Locations:
Microsoft Teams, or
SAS Institute, Havneholmen 8, 2450 København SV
SAS Institute, Frederiks Plads 36 4., 8000 Aarhus C
SAS Institute, Stora Frösunda Gård, 169 70 Solna
Register: Denmark / Finland / Norway / Sweden
The join link will be sent to you before the meeting.
Agenda
Breakfast (8.30-9.00 am)
Will be updated…
If you have any questions, do not hesitate to give us a call or send us an email:
Henrik Koch
Fraud Practice Nordics
T: +45 27 25 28 03
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