About Kiteulf

Kiteulf · ‎11-09-2018

I am getting an error due to the fact that the one variable is not working &ID&nID what am I doing wrong? %put &ID1; 810034882 33 %put &ID2; 810182482 34 %put &ID3; 810724412 35 %put &ID1; 810034882 36 %put &nID; 3 37 38 %macro loop; 39 40 %do i= 1 %to &nID; 41 42 43 Proc sql; 44 create table bs_company_&ID&NID as 45 select distinct &ID&NID as orgnbr 46 ,t0.c 47 ,t0.c1 48 ,t0.c2 49 50 , t1.x 51 ,t1.xxx 52 ,t1.xxxx 53 ,t0.xxx1 54 ,t0.xxx2 55 ,t0.xxx3 56 ,t0.xxx4 57 ,t0.xxx5 58 59 from bs_pre_company as t0 60 left join s18_19.startfile2 as t1 61 on &ID&NID=t1.orgnbr 62 63 64 65 66 67 ; 68 quit; 69 70 71 %END; 72 %MEND LOOP; 73 %LOOP; WARNING: Apparent symbolic reference ID not resolved. NOTE: Line generated by the invoked macro "LOOP". 73 &ID&NID as select distinct _ 22 200 WARNING: Apparent symbolic reference ID not resolved. ERROR 22-322: Syntax error, expecting one of the following: (, '.', AS, LIKE. ERROR 200-322: The symbol is not recognized and will be ignored. NOTE: Line generated by the invoked macro "LOOP". 73 &ID&NID as organisationregistrationnbr _ 22 73 ! ,t0.company_customer_id ,t0.SourceSystId as Company_sourcesystid ,t0.contractnbr as company_contractnbr 73 ! ,input(put WARNING: Apparent symbolic reference ID not resolved. NOTE: Line generated by the invoked macro "LOOP". 73 &ID&NID=t1.organisationregistrationnbr where _ 22 ERROR 22-322: Syntax error, expecting one of the following: a name, a quoted string, a numeric constant, a datetime constant, a missing value, BTRIM, INPUT, PUT, SUBSTRING, USER. NOTE: PROC SQL set option NOEXEC and will continue to check the syntax of statements. NOTE: The SAS System stopped processing this step because of errors. NOTE: PROCEDURE SQL used (Total process time): real time 0.00 seconds cpu time 0.01 seconds

Kiteulf · ‎04-18-2018

Hi I have the following ; InvestedAmount = 1400000; Amount = 1300000; Cashpayment = 100000; DP = Cashpayment/Investedamount; Scorevalue = 725 SigMod_DPSCORE = (982498.1617 +(357322.7098/(1+exp(-(DP-0.0641)/0.0545))))*0.61477534426774; Sigmod_Score=1333381.0933*0.8008430656372; Linear_reg_constant =-501604.719938709; Minimize DP with SigMod_DPSCORE+Sigmod_Score+Linear_reg_constant being equal to InvestedAmount Is there any other information that is needed? I did; SigMod_SCORE = 712072.4496 +(638693.1194/(1+exp(-(ScoreValue-595.1628)/36.3054))); SCORE_weight = 0.8008430656372; DP_weight = 0.61477534426774; SCB_part = SigMod_SCORE*SCORE_weight; Linear_reg_constant =-501604.719938709; Calc1 = Amount+(Linear_reg_constant*-1); Calc2 = (Calc1-SCB_part)/DP_weight; Y2= 982498.1617; a2= 357322.7098; b2 =0.0545; x2=0.0641; Calc_Y1 =Y2*(1)+a2; calc_Y2 =(Calc_Y1-Calc2)*-1; calc_Y3 = Y2-calc2; calc_y4 =calc_Y2/calc_y3; calc_y5 =log(calc_y4); calc_y6 =(-1*b2)*calc_y5; Required_eq_pct =calc_y6+x2; If Required_eq_pct GT downpayment_pct then do; Required_add_equity= ceil(((sum(cashpayment,amount)*Required_eq_pct)-cashpayment)); However Required_add_equity doesn't take into the consideration that there is a constraint to keep Investedamount stable/equal. So How can I do this with respect to minimizing DP?

Kiteulf · ‎03-15-2018

DATA want; set have; by id; retain vintage; if first.id then vintage= 1*(1-Depreciation); vintage =vintage*(1-Depreciation); run;

Kiteulf · ‎03-15-2018

data have; input YearMonth ID depreciation; datalines; 201511 1 1 201512 1 0.012717037 201601 1 0.012756447 201602 1 0.012413319 201603 1 0.012417115 201604 1 0.012061455 201605 1 0.011910294 201606 1 0.011778051 201607 1 0.0119076 201608 1 0.011796668 201609 1 0.011721272 201610 1 0.011778189 201611 1 0.011829325 201612 1 0.01178267 201701 1 0.011570935 201702 1 0.011419379 201703 1 0.011254156 201704 1 0.011193984 201705 1 0.011112798 201706 1 0.011096301 201707 1 0.011058088 201708 1 0.01101701 201709 1 0.011440038 201710 1 0.011520155 201711 1 0.01152442 201712 1 0.01143082 201604 2 1 201605 2 0.011477848 201606 2 0.006636087 201607 2 0.013963745 201608 2 0.013915906 201609 2 0.014880584 201610 2 0.012836766 201611 2 0.014111002 201612 2 0.012796802 201701 2 0.011764952 201702 2 0.01255818 201703 2 0.012798133 201704 2 0.012469151 201705 2 0.01328034 201706 2 0.013028762 201707 2 0.012920913 201708 2 0.012739095 201709 2 0.012776933 201710 2 0.012114558 201711 2 0.011621488 201712 2 0.011033519 ;run; data want; input YearMonth ID depreciation vintage; datalines; 201511 1 1 1 201512 1 0.012717037 0.987282963 201601 1 0.012756447 0.97468874 201602 1 0.012413319 0.962589617 201603 1 0.012417115 0.950637031 201604 1 0.012061455 0.939170965 201605 1 0.011910294 0.927985163 201606 1 0.011778051 0.917055307 201607 1 0.0119076 0.90613538 201608 1 0.011796668 0.895446002 201609 1 0.011721272 0.884950235 201610 1 0.011778189 0.874527124 201611 1 0.011829325 0.864182058 201612 1 0.01178267 0.853999687 201701 1 0.011570935 0.844118112 201702 1 0.011419379 0.834478807 201703 1 0.011254156 0.825087452 201704 1 0.011193984 0.815851436 201705 1 0.011112798 0.806785044 201706 1 0.011096301 0.797832714 201707 1 0.011058088 0.78901021 201708 1 0.011017012 0.780317676 201709 1 0.011440038 0.771390813 201710 1 0.011520155 0.762504271 201711 1 0.01152442 0.753716851 201712 1 0.01143082 0.74510125 201604 2 1 1 201605 2 0.011477848 0.988522152 201606 2 0.006636087 0.981962233 201607 2 0.013963745 0.968250363 201608 2 0.013915906 0.954776282 201609 2 0.014880584 0.940568653 201610 2 0.012836766 0.928494793 201611 2 0.014111002 0.915392801 201612 2 0.012796802 0.903678701 201701 2 0.011764952 0.893046964 201702 2 0.01255818 0.88183192 201703 2 0.012798133 0.870546117 201704 2 0.012469151 0.859691147 201705 2 0.01328034 0.848274156 201706 2 0.013028762 0.837222194 201707 2 0.012920913 0.826404519 201708 2 0.012739095 0.815876873 201709 2 0.012776933 0.805452469 201710 2 0.012114558 0.795694768 201711 2 0.011621488 0.786447611 201712 2 0.011033519 0.777770326 ; run;

Kiteulf · ‎03-15-2018

YearMonth ID depreciation Want 201511 1 1 1 201512 1 0,012717037 0,987283 201601 1 0,012756447 0,974689 201602 1 0,012413319 0,96259 201603 1 0,012417115 0,950637 201604 1 0,012061455 0,939171 201605 1 0,011910294 0,927985 201606 1 0,011778051 0,917055 201607 1 0,0119076 0,906135 201608 1 0,011796668 0,895446 201609 1 0,011721272 0,88495 201610 1 0,011778189 0,874527 201611 1 0,011829325 0,864182 201612 1 0,01178267 0,854 201701 1 0,011570935 0,844118 201702 1 0,011419379 0,834479 201703 1 0,011254156 0,825087 201704 1 0,011193984 0,815851 201705 1 0,011112798 0,806785 201706 1 0,011096301 0,797833 201707 1 0,011058088 0,78901 201708 1 0,01101701 0,780318 201709 1 0,011440038 0,771391 201710 1 0,011520155 0,762504 201711 1 0,01152442 0,753717 201712 1 0,01143082 0,745101 201604 2 1 1 201605 2 0,011477848 0,988522 201606 2 0,006636087 0,981962 201607 2 0,013963745 0,96825 201608 2 0,013915906 0,954776 201609 2 0,014880584 0,940569 201610 2 0,012836766 0,928495 201611 2 0,014111002 0,915393 201612 2 0,012796802 0,903679 201701 2 0,011764952 0,893047 201702 2 0,01255818 0,881832 201703 2 0,012798133 0,870546 201704 2 0,012469151 0,859691 201705 2 0,01328034 0,848274 201706 2 0,013028762 0,837222 201707 2 0,012920913 0,826405 201708 2 0,012739095 0,815877 201709 2 0,012776933 0,805452 201710 2 0,012114558 0,795695 201711 2 0,011621488 0,786448 201712 2 0,011033519 0,77777

Kiteulf · ‎03-15-2018

How can i do DATA Want; set Have; by id; if first.id then total_vintage =1+depreciation; total_vintage+depreciation; run; Which works fine, but if I want to do the following calculation by id; total_vintage*(1-depreciation); ???

Kiteulf · ‎03-01-2018

I have this type of data: 125628,59000,.,.,.,. .,50000,.,.,.,. using prx=prxparse("s/.,[., ]*/, /"); I get 12562, 5900, , , , . , 5000, , , , . I would like to have 125628,59000 50000

Kiteulf · ‎03-01-2018

Hi I am trying to concatenate data which have the form RegAdjusted mean_objectprice_month2 regperiod2 mean_objectprice_month3 regperiod3 mean_objectprice_month4 regperiod4 mean_objectprice_month5 regperiod5 mean_objectprice_month6 regperiod6 mean_objectprice_month7 regperiod7 AA49918 187000 201010 80000 201501 AA50059 135000 201703 120000 201712 AA50067 106250 201308 AA50074 152600 201309 149000 201407 145000 201408 AA50085 150000 201106 AA50114 270000 201101 AA50221 387000 201101 AA50235 270000 201211 AA50237 96500 201601 AA50262 64535 201406 75000 201602 AA50291 39000 201703 AA50457 24035 201408 AA50497 158000 201002 158000 201002 AA50506 79000 201301 AA50644 49977 201410 AA50689 299980 201301 AA50768 160000 201703 AA50828 69977 201606 AA50830 150500 201508 AA50840 118000 201402 100000 201801 AA50856 91873,5 201108 AA50949 125000 201307 AA51050 95000 201612 AA51061 144950 201107 AA51137 65000 201207 AA51151 189000 201709 AA51167 89000 201310 AA51194 326438 201402 300000 201404 190000 201409 214500 201411 299900 201501 AA51223 45000 201106 45000 201106 AA51272 179500 201509 AA51285 35000 201607 AA51296 131000 201405 AA51358 80535 201503 AA51388 285000 201512 280000 201605 AA51392 140000 201211 AA51404 310000 201701 AA51447 273000 201510 AA51466 84977 201408 67000 201710 AA51479 40000 201711 AA51563 208000 201201 129500 201605 129500 201605 125000 201608 To look something like this RegAdjusted Price1 Period1 Price2 Period2 Price3 Period3 Price4 Period4 Price5 Period5 Price6 Period6 AA49918 187000 201010 80000 201501 AA50059 135000 201703 AA50067 106250 201308 AA50074 152600 201309 149000 201407 145000 201408 AA50085 150000 201106 AA50114 270000 201101 AA50221 387000 201101 AA50235 270000 201211 AA50237 96500 201601 AA50262 64535 201406 75000 201602 AA50291 39000 201703 AA50457 24035 201408 AA50497 158000 201002 158000 201002 AA50506 79000 201301 AA50644 49977 201410 AA50689 299980 201301 AA50768 160000 201703 AA50828 69977 201606 AA50830 150500 201508 AA50840 118000 201402 AA50856 91873,5 201108 AA50949 125000 201307 AA51050 95000 201612 AA51061 144950 201107 AA51137 65000 201207 AA51151 189000 201709 AA51167 89000 201310 AA51194 326438 201402 300000 201404 190000 201409 214500 201411 299900 201501 AA51223 45000 201106 45000 201106 AA51272 179500 201509 AA51285 35000 201607 AA51296 131000 201405 AA51358 80535 201503 AA51388 285000 201512 280000 201605 AA51392 140000 201211 AA51404 310000 201701 AA51447 273000 201510 AA51466 84977 201408 67000 201710 AA51479 40000 201711 AA51563 208000 201201 129500 201605 129500 201605 125000 201608 Trying with call catx and then split, but I can't get it to work

Kiteulf · ‎01-16-2018

Hi How do I match the different values in on my main dataset I want to match in the Number given that the DP_pct/score is over or below the thresholdvalues DP_pct Score Number 0,05 523 0 0,1 523 0 0,2 523 0 1 523 0 0,05 541 0 0,1 541 100 000 0,2 541 200 000 1 541 300 000 0,05 561 100 000 0,1 561 200 000 0,2 561 300 000 1 561 400 000 0,05 615 500 000 0,1 615 600 000 0,2 615 800 000 1 615 1 000 000 0,05 1 000 700 000 0,1 1 000 800 000 0,2 1 000 1 000 000 1 1 000 1 000 000

Kiteulf · ‎09-14-2017

Sry Just need to sort the other way and go with the last 7 obs

Kiteulf · ‎09-14-2017

yes that was the idea , by contract_month, by contract

Kiteulf · ‎09-14-2017

I am trying to get the next 6 observations, by contract_month, so that if bad is one , then my result should be one. like ContractNbr underlying Bad mob contract_month Result 1 1 0 3 20000861-201402 0 1 1 0 4 20000861-201403 1 1 1 0 5 20000861-201404 1 1 1 0 6 20000861-201405 1 1 1 0 7 20000861-201406 1 1 2 0 8 20000861-201407 1 1 2 0 9 20000861-201408 1 1 3 1 10 20000861-201409 1 1 3 1 11 20000861-201410 1 1 3 1 12 20000861-201411 1 1 4 1 13 20000861-201412 1 1 4 1 14 20000861-201501 1 1 4 1 15 20000861-201502 1 1 5 1 16 20000861-201503 1 1 6 1 17 20000861-201504 1 1 5 1 18 20000861-201505 1 1 6 1 19 20000861-201506 1 1 7 1 20 20000861-201507 1 1 8 1 21 20000861-201508 1 1 1 0 22 20000861-201509 1 1 2 0 23 20000861-201510 1 1 3 1 24 20000861-201511 1 1 3 1 25 20000861-201512 0 1 2 0 26 20000861-201601 0 1 0 0 27 20000861-201602 0 1 0 0 28 20000861-201603 0 1 0 0 29 20000861-201604 0 1 1 0 30 20000861-201605 1 1 1 0 31 20000861-201606 1 1 1 0 32 20000861-201607 1 1 1 0 33 20000861-201608 1 1 2 0 34 20000861-201609 1 1 2 0 35 20000861-201610 1 1 3 1 36 20000861-201611 1 1 0 0 37 20000861-201612 1 1 1 0 38 20000861-201701 1 1 2 0 39 20000861-201702 1 1 3 1 40 20000861-201703 0 1 0 0 41 20000861-201704 0 1 0 0 42 20000861-201705 0 1 0 0 43 20000861-201706 0 1 0 0 44 20000861-201707 0 1 0 0 45 20000861-201708 0 In excel the formula is like =IF(SUM(C3:C8)>=1;1;0)

Kiteulf · ‎08-24-2017

ods html file='test.html' path='\\***\**\**\***\***\' (url=none); proc sgplot data=Badrates_TotalPolicy_ave subpixel noborder; styleattrs datacontrastcolors=(Green Gold Red) datalinepatterns=(1) datasymbols=(circlefilled trianglefilled); series x=Logg_date y=mov_tot_6 / group=TotalPolicy lineattrs=(thickness=3 ); series x=Logg_date y=mov_tot_6 / group=TotalPolicy lineattrs=(thickness=3 ); series x=Logg_date y=mov_tot_6 / group=TotalPolicy lineattrs=(thickness=3 ); xaxistable _FREQ_ / class=TotalPolicy location=outside colorgroup=TotalPolicy; xaxis display=(nolabel); yaxis label='BadRate'; run; ods html close;

Kiteulf · ‎08-23-2017

proc sgplot data=Badrates_TotalPolicy_ave subpixel noborder; series x=Logg_date y=mov_tot_6 / group=TotalPolicy lineattrs=(thickness=3 ); series x=Logg_date y=mov_tot_6 / group=TotalPolicy lineattrs=(thickness=3 ); series x=Logg_date y=mov_tot_6 / group=TotalPolicy lineattrs=(thickness=3 ); xaxistable _FREQ_ / class=TotalPolicy location=outside colorgroup=TotalPolicy; xaxis display=(nolabel); yaxis label='BadRate'; run; How do I control the colors on the TotalPolicy so that top series is green, 2nd is yellow and 3rd is red? And the same for the table?

Kiteulf · ‎08-18-2017

Yeah I want to use the Group option, but found it hard to implement as my data is of the type reponsecolumn1 responsecolumn2 1 1 0 1 0 0 1 0 How do I get it to a one response column and a classifier?

Online Status	Offline
Date Last Visited	‎01-19-2023 07:02 AM

Re: Group by to summarize values

Re: Group by to summarize values

Re: Group by to summarize values

Re: Group by to summarize values

Re: Group by to summarize values

Group by to summarize values

Re: Formatting of sas datetime

Re: Formatting of sas datetime

Re: Formatting of sas datetime

Formatting of sas datetime

Re: Nested looping

Re: Mulitplication

Re: Color control

Formatting of sas datetime

Re: Color control

Sas macro loop

optimization plus constraint

Re: Mulitplication

Re: Mulitplication

Re: Mulitplication

Mulitplication

Prxparse

Data replacing

Proc sql thresholdvalues

Re: proc sql with max (case when...

Re: proc sql with max (case when...

proc sql with max (case when...

Re: Color control

Color control

Re: sgplot with Multiple variables on vbar