Hi Forum, I have a variable named "ninety" in the attahced file. I need to forecast its values for maximum possible length ahead as dictated by my 24 month's actual observations. I have tried various methods such as moving average (3point, 12point), weighted moving average, exponential smoothing etc. but the Percent Absolue Deviation between predicted and actual values are way too high. So, I tried ARIMA as the last resort.   Honestly I do not have any previous ARIMA expereince, so I have followed the SAS documentation mecahnically and followed the steps. Question: I cannot run the last two steps to get the final forecasts. Could someone please help? Thanks, Mirisage /*taking the graph*/ ods graphics on; proc sgplot data=test;    scatter y=ninety x=current_date; run; /*Analyzing correlation properties*/ proc arima data=test ;    identify var=ninety nlag=6; run; /*White Noise Test*/ proc arima data=test ;    identify var=ninety nlag=6; run; proc arima data=test ;    identify var=ninety nlag=5; run; proc arima data=test ;    identify var=ninety nlag=4; run; proc arima data=test ;    identify var=ninety nlag=3; run; /*Since the series is nonstationary, I transformed it to a stationary series by differencing.*/ /*Identification of the Differenced Series*/ proc arima data=test;    identify var=ninety(1); run; /*The autocorrelations decrease rapidly in this plot, indicating that the change in ninety is a stationary time series. */ /*not running*/ proc arima data=test; estimate p=1;    run; /*Not running*/    /*forecasting*/ proc arima data=test;    forecast lead=12 interval=month id=date out=results;    run; ... View more

Hi Collegues, I have the attached data set. Table 1 Column D calculates the roll rate of outstanding balance from delinquency cycle_1 to cycle_1. Table 1 Cell c28 shows the moving sum equation I have used to forecast the value of that cell based on previous 24 months actual data. Column N of Table 2 applies the same forecasting equation for a known data range and column P calculates how well our prediction equation does the forecasting. Sad to say that the % absolute deviation is way too unacceptable. Could any one help me to improve this equation to increase the forecasting precision. Thanks Mirisage ... View more

Hi Forum, I am using SAS EG 4.3. I just double click EG Icon; open EG;then get the SAS editor embedded in it; and then do the SAS work as if I would do in a SAS PC version. I want to know what is the exact version of SAS I am working within  the EG 4.3. Could anyone please let me know how to find it. Thank you Mirisage ... View more

Hi Community, I have this data set. I havve categorised the "inocome" variable and got the freq distribution. It gives the last output table shown at the bottom. Q: I need to get the freq band for zeros seperately. At present "Income_Range" column of output table (see the bottom) categorises "zero" within " -7 to 0" income band. But we like to impose a "0" income band separately. Could anyone help me for coding. Thanks Mirisage Data have; input income; cards; 0 15 . 392 219 95 208 -10 12 41 22 65 372 360 0 0 0 393 190 . 0 0 0 168 93 -8 0 14 43 138 52 125 0 -9 45 ; run; data want; length Income_Range $20; set have; if Income = . then Income_Range='Missing'; else if Income   <=-9   then Income_Range = '<=-9'; else if Income   <=-8   then Income_Range = '-8 to -9'; else if Income   <=-1   then Income_Range = '-1 to -8'; else if Income   <=0  then Income_Range ='-7 to 0'; else if Income   <=41 then  Income_Range ='1-41'; else if Income   <=392 then  Income_Range ='42-392'; else Income_Range = '>392'; run; proc freq data=want; tables Income_Range; run;                  Income_Range Frequency Percent Cumulative Cumulative Frequency Percent -7 to 0 9 25.71 9 25.71 -8 to -9 1 2.86 10 28.57 1-41 5 14.29 15 42.86 42-392 15 42.86 30 85.71 <=-9 2 5.71 32 91.43 >392 1 2.86 33 94.29 Missing 2 5.71 35 100.00 ... View more

Hi Forum, I have taken the freq distribution of a variable named “income” employing this code (for confidentiality I cannot attach the data set). data want; length Income_Range $15; set have; if Income_ = . then Income_Range='Missing'; else if Income_   <=0   then Income_Range = '<=0'; else if Income_   <=80 then  Income_Range ='>0 to <=80'; else if Income_   <=100 then  Income_Range ='>80 to <=100'; else Income_Range = '>100'; run; proc freq data=want;   tables Income_Range; run; Question: However much I tried, the output table comes with “Income_Range” bands being jumped (meaning there are not in sequence). Could anyone please let me know any reason for this? Income_Range Frequency Percent Cumulative Cumulative Frequency Percent <=0 82678 5.23 82678 5.23 >0 to <=80 1108529 70.12 1191207 75.35 >100 68658 4.34 1259865 79.69 >80 to <=100 321081 20.31 1580946 100 The sequence of Income_Range column of above table should have been like below. Income_Range <=0 >0 to <=80 >80 to <=100 >100 Thank you for any help. Mirisage ... View more