Using the Case clause with Model clause

Question

Hello PL SQL gurus
I've used some scripts I've found on these forums to create a mortgage amortization statement. What I am trying to accomplish is getting the script to run a calculation or use a value within a table based upon the value in that table.
Here are the two tables:
CREATE TABLE mortgage_facts (customer VARCHAR2(20), fact VARCHAR2(20),
amount NUMBER(10,3));
INSERT INTO mortgage_facts VALUES ('Smith', 'Loan', 131828.81);
INSERT INTO mortgage_facts VALUES ('Smith', 'Annual_Interest', 3.348);
INSERT INTO mortgage_facts VALUES ('Smith', 'Payments', 72);
INSERT INTO mortgage_facts VALUES ('Smith', 'PaymentAmt', 0);
CREATE TABLE mortgage (customer VARCHAR2(20), pmt_num NUMBER(4), principalp NUMBER(10,3), interestp NUMBER(10,3), mort_balance NUMBER(10,3));
INSERT INTO mortgage VALUES ('Smith',0, 0, 0, 131828.81);
If the value within the table mortgage_facts is zero, I want the script to run a calculation to be used in a MODEL clause. If it is not zero, I would like to use that value instead of the calculation. Below is the script that I am getting an error on (I have bolded the portion in question):
SELECT c, p, to_char(round(m,2),'fm$9999999.00') principal_balance,
to_char(round(pp,2),'fm$9999999.00') towards_principal,
to_char(round(ip,2),'fm$9999999.00') towards_interest,
to_char(round(mp,2),'fm$9999999.00') monthly_payment
FROM MORTGAGE
MODEL --See 1
IGNORE NAV
REFERENCE R ON
*(SELECT customer, fact, amt --See 2*
FROM mortgage_facts
*MODEL DIMENSION BY (customer, fact) MEASURES (amount amt)          --See 3*
RULES SEQUENTIAL ORDER
CASE WHEN mortgage_facts.fact = 'PaymentAmt' AND mortage_facts.amt = 0 THEN
*amt[ANY, 'PaymentAmt'] = mortgage_facts.amt*
ELSE
*amt[any, 'PaymentAmt']= (amt[CV(),'Loan']**
*Power(1+ (amt[CV(),'Annual_Interest']/100/12),*
*amt[CV(),'Payments']) **
*(amt[CV(),'Annual_Interest']/100/12)) /*
*(Power(1+(amt[CV(),'Annual_Interest']/100/12),*
*amt[CV(),'Payments']) - 1)*
END
DIMENSION BY (customer cust, fact) measures (amt)
MAIN amortization
PARTITION BY (customer c)
DIMENSION BY (0 p)
MEASURES (principalp pp, interestp ip, mort_balance m, customer mc, 0 mp )
RULES SEQUENTIAL ORDER
ITERATE(1000) UNTIL (ITERATION_NUMBER+1 =
r.amt[mc[0],'Payments'])
(ip[ITERATION_NUMBER+1] = m[CV()-1] *
r.amt[mc[0], 'Annual_Interest']/1200,
mp[ITERATION_NUMBER+1] = r.amt[mc[0], 'PaymentAmt'],
pp[ITERATION_NUMBER+1] = r.amt[mc[0], 'PaymentAmt'] - ip[CV()],
m[ITERATION_NUMBER+1] = m[CV()-1] - pp[CV()]
ORDER BY c, p
Any help is much appreciated. Thank you!!

Answer 1

Ok, here we go, one way with iterative model:
select *
from mortgage_facts
model
partition by (Customer)
dimension by (1 p)
measures(loan, payments, INTEREST, PAYMENTAMT, INTERESTPMT, PRINCIPALPMT, balance)
rules iterate(1e9) until (iteration_number+2 >= payments[1])
(loan[iteration_number+2]=loan[1]
,payments[iteration_number+2]=cv(p)-1
,interest[iteration_number+2]=interest[1]
,paymentamt[iteration_number+2]=ROUND(
  (LOAN[1] * (INTEREST[1]/12/100)*Power((1+INTEREST[1]/12/100), PAYMENTS[1])/(Power((1+INTEREST[1]/12/100),PAYMENTS[1])-1)), 2)
,INTERESTPMT[iteration_number+2]=round(balance[cv(p)-1]*interest[1]/1200, 2)
,PRINCIPALPMT[iteration_number+2]=paymentamt[cv()]-INTERESTPMT[cv()]
,balance[iteration_number+2]=balance[cv()-1]-PRINCIPALPMT[cv()]
CUSTOMER     P     LOAN     PAYMENTS     INTEREST     PAYMENTAMT     INTERESTPMT     PRINCIPALPMT     BALANCE
Smith     1     131828.81     72     3.348     0     0     0     131828.81
Smith     2     131828.81     1     3.348     2023.55     367.8     1655.75     130173.06
Smith     3     131828.81     2     3.348     2023.55     363.18     1660.37     128512.69
Smith     4     131828.81     3     3.348     2023.55     358.55     1665     126847.69
Smith     5     131828.81     4     3.348     2023.55     353.91     1669.64     125178.05
Smith     6     131828.81     5     3.348     2023.55     349.25     1674.3     123503.75
Smith     7     131828.81     6     3.348     2023.55     344.58     1678.97     121824.78
Smith     8     131828.81     7     3.348     2023.55     339.89     1683.66     120141.12
Smith     9     131828.81     8     3.348     2023.55     335.19     1688.36     118452.76
Smith     10     131828.81     9     3.348     2023.55     330.48     1693.07     116759.69
Smith     11     131828.81     10     3.348     2023.55     325.76     1697.79     115061.9
Smith     12     131828.81     11     3.348     2023.55     321.02     1702.53     113359.37
Smith     13     131828.81     12     3.348     2023.55     316.27     1707.28     111652.09
Smith     14     131828.81     13     3.348     2023.55     311.51     1712.04     109940.05
....