About user24feb

user24feb · ‎02-12-2016

No, you can't difference a series that is already stationary. If you look at the IACF it is slowly decreasing: Data A; Do i=1 To 100; u=IfN(Ranuni(1) gt 0.5,1,0); Output; End; Run; ODS Graphics On; Proc Arima; Identify Var=u(1); Run; ODS Graphics Off;

user24feb · ‎02-04-2016

Hm, you are right. This code will work (but if it was my code, I would not define Trans_cd with a comma in the first place): Data Cust_Transaction; Length Trans_Type_CD $6.; Trans_Type_CD='DFEE'; Output; Trans_Type_CD='1387-D'; Output; Trans_Type_CD='1419-D'; Output; Run; %MACRO test(cd); %Put **CHECK**&cd.**; Proc SQL; Create Table AAA as SELECT DISTINCT * FROM Cust_Transaction Where (Trans_Type_CD in (%Sysfunc(TranWrd("&cd.",%Str(, ),%Str(", "))))) ;QUIT; %MEND; %let Trans_cd = 1387-D, 1419-D, 1383-D; %test(%BQuote(&Trans_cd.));

user24feb · ‎02-04-2016

Replace the Where-line with: Where (Trans_Type_CD in (%Sysfunc(TranWrd("&cd.",%Str(, ),%Str(", ")))))

user24feb · ‎02-03-2016

10 minutes computing time is somewhat strange. I don't think hashing would be faster to get the max value than proc means or so. Is there something special about your data set? Options Fullstimer; Data A; Do i=1 To 1e7; * 10 million rows; x=Rannor(1); Output; End; Run; Proc SQL; Select Max(x) From A; Quit; Proc Means Data=A Max; Var x; Run; Data _NULL_; Length x 8.; If _N_ eq 1 Then Do; Declare Hash H (Dataset:'A (Keep=x)',Hashexp:20); Declare HIter HI ('H'); H.Definekey('x'); H.Definedone(); Call Missing (x); End; Retain Max; rc=HI.First(); Do While (not rc); Max=IfN(x gt Max,x,Max); rc=HI.Next(); End; If rc Then Put Max; Run;

user24feb · ‎01-22-2016

I hope this question is admissible as it is not about SAS-syntax, but about the meaning of Rick_SAS's & Ksharp's line of code? The ifn-part, of course, is clear, I am looking for a substantial interpretation or a source of this formula: _RATE_= ifn((prob<=&peak),prob,2*&peak-prob) The complete program was: %let peak=0.7; title 'Simulation from Normal'; data normal; call streaminit(1234); do i=1 to 100000; x=rand('normal'); prob = cdf("Normal", x); _RATE_= ifn((prob<=&peak),prob,2*&peak-prob); * <-- distribution function of PERT?? ; output; end; drop prob ; run; proc surveyselect data=normal out=want method=PPS_WR N=10000; size _RATE_; /* specify the probability variable */ run; proc sgplot data=want; histogram x; density x/type=kernel; run; The original post was: https://communities.sas.com/t5/SAS-Statistical-Procedures/Change-statistical-moments-parameters-of-a-sample/m-p/243746#U243746 Thanks&kind regards

user24feb · ‎01-18-2016

I believe that you are trying to access the log (?) Proc PrintTo Log="D:\xxx.LOG" New; Run; Data _NULL_; x=IntNX('month',2,'01JAN2016'); * d missing; Run; Proc PrintTo; Run; Data Errors (Drop=Line); Infile "D:\xxx.LOG" Delimiter='09'x Missover End=Eof; Informat Line $200.; Input Line; Retain MyError 0; If Find(UpCase(Line),'_ERROR_=1') Then MyError=1; If Eof Then Output; Run;

user24feb · ‎01-18-2016

I would like to resample existing data. (PERT would be nice too, but for my purpose a triangular dist. is sufficient)

user24feb · ‎01-18-2016

Unfortunately, I only have STAT/ETS and OR, but I think I can build something similar. If there is something similar for those modules, please let me know.

user24feb · ‎01-15-2016

This is a very crude code, but it should show the basic idea. The actual data are "recipes" (a big number of bill of materials consisting of different components with 'interesting areas'). This is, sampling the multivariate case for general distributions (not symmetric) and correlation (because the percentages of the components add up to 100 %) would be complete description. A SAS function for this is probably to much to hope for, but there might be articles about this problem. * Defines allowed values; Data A; Do i=1 To 1000; X=Round(Rannor(1)*3+10,0.01); Output; End; Run; * is not skewed ..; Proc Means Data=A Mean StdDev Skewness; Var X; Run; * 'nasty' way to get a kind of a triangular distribution; Data B; Set A; Select ; When (X > 6 & X <= 7) Group=1; When (X > 7 & X <= 8) Group=2; When (X > 8 & X <= 9) Group=3; When (X > 9 & X <= 10) Group=4; Otherwise Group=0; End; Run; Proc Sort Data=B; By Group X; Run; * sample sizes give left skewed distribution ..; Proc SurveySelect Data=B Out=C Method=srs N=(0 5 5 10 30); Strata Group; Run; Proc Means Data=C Mean StdDev Skewness; Var X; Run;

user24feb · ‎01-15-2016

Hello, Is possible (and how) to take sample - similar to proc surveyselect -, but change certain statistical parameters of the sample? For example, take a normal distribution (uniform distribution is a bad example) and then get a triangular-distributed sample which has a certain mode? Thanks&kind regards

user24feb · ‎01-12-2016

It is possible to replicate this error for example: Libname sqlstage ODBC Schema=DBO DSN=sqlstage; Proc SQL; *Drop Table sqlstage.Test_x_3; Create Table sqlstage.Test_x_3 (Var Float); Create Table sqlstage.Test_x_4 As Select * From sqlstage.Test_x_3 (Drop=Var); Quit; Gives: ERROR: Table SQLSTAGE.Test_x_3 doesn't have any columns. PROC SQL requires each of its tables to have at least 1 column. Could it be that there actually are no columns or that the user simply hasn't the permission to access this table?

user24feb · ‎01-08-2016

Hello, I might have overlooked something (summary output?), but is there a standard option which only gives me the lowest level (=raw materials) of a bom and filters out the intermediate products. Does it exist and is there an example for it? I mean the data step at the end: Data PS; Input @1 Material $7. @9 Component $7. @17 Qty 8.; Datalines; 2001234 4601234 0.3 2001234 4601235 0.2 2001234 4601236 0.4 2001234 4100001 0.05 2001234 4000000 0.15 4601234 4000123 0.5 4601234 4000124 0.5 4601235 8000123 1 4601236 4500000 0.8 4601236 4500001 0.2 ; Run; Proc SQL; Create Table PS_2 As Select Distinct a.Component As Material, '' As Component Length=7, . As Qty From PS a Left Join PS b On a.Component=b.Material Where Missing (b.Material); Quit; Proc Append Base=PS Data=PS_2; Run; Proc BOM Data=PS Out=Res; Structure / Parent=Material Component=Component Quantity=Qty EndItem=('2001234'); Run; * Standard procedure which is quicker than this ?; Data Res; Length Lowest $3.; Set Res End=Eof; If not Eof Then Set Res (Firstobs=2 Keep=_LEVEL_ Rename=(_LEVEL_=_LEVEL_SUCC_)); If _LEVEL_ ge _LEVEL_SUCC_ Then Lowest='YES'; Run; Thanks&kind regards

user24feb · ‎12-18-2015

The add method adds entries, and the replace method removes but also adds entries. Maybe this program helps a little: * Copy-Paste-Problem ..; ** &colon; is equal to ":", sorry, this never happened before ; Data A; Length N $1.; Do N='A','B','C'; Do X=1 To 5; Output; End; End; Run; Data _NULL_; Length N $1. X 8; Declare Hash H (Dataset:'A',Multidata&colon;'y'); H.Definekey('N'); H.Definedata(All:'y'); H.Definedone(); * This is what add does; N='X';X=8; rc=H.Add(Key:N,Data&colon;N,Data&colon;X); H.Output(Dataset:'B'); * This is what replace does; N='B';X=9; rc=H.Replace(Key:N,Data&colon;N,Data&colon;X); H.Output(Dataset:'C'); Run;

user24feb · ‎12-18-2015

Because the concatenation operator only puts character variables "next to each other". The resulting variable has the length of all the connected variables. Because the you didn't define the length of your character variables, they all have the same length. Thus, you either have to trim or define a longer variable (which would contain lots of spaces; would be MiddleInitial3 below). data Names; infile datalines dlm='@'; input Name:$32.; datalines; Harry Micheal Henderson Larry Kerry Baldwin Jerry m. Stout ; data SplitNames; set Names; length Last $8 MiddleInitial3 $33.; First = Scan(name,1); FirstName = trim(First); /* Trim functions doesn't seem to have any effect */ Middle = Scan(name,2); MiddleIntial = upcase(substr(Middle,1,1)); MiddleIntial = trim(MiddleIntial)||"."; MiddleIntial2 = upcase(substr(Middle,1,1)); MiddleIntial2_Length=Length(MiddleIntial2); MiddleIntial2 = MiddleIntial2||"."; MiddleInitial3=MiddleIntial2||"."; Last = Scan(name,3); label MiddleIntial="Middle Intital"; drop Middle; run;

user24feb · ‎11-25-2015

If you insist on proc means you would need some numeric dummy variable: Data Have; Input Company $ Year Country_of_operations $; If not Missing (Country_of_operations) Then Flag=1; Datalines; A 2000 GBR A 2000 GBR A 2000 USA A 2001 FRA A 2002 USA A 2002 KSA A 2002 RUS A 2002 KSA A 2003 . B 2000 . ; Proc Sort Data=Have Nodupkey; By Company Year Country_of_operations; Run; Proc Means Data=Have NoPrint; Label Flag='Number of ..'; By Company Year; Var Flag; Output Out=Want (Drop=_: ) Sum=; Run;

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