appendForPrediction

appendForPrediction(engine, data)

engine is a string indicating the name of the yield curve engine or the engine object returned by createYieldCurveEngine.

data is a table object containing data to be predicted. Its schema must match the predictDummyTable parameter specified in createYieldCurveEngine.

Append data to the predictDummyTable of a yield curve engine (createYieldCurveEngine) for prediction.

Create a yield curve engine.

dummyTable = table(1:0, `symbol`sendingtime`askDirtyPrice1`bidDirtyPrice1`midDirtyPirce1`askyield1`bidyield1`midyield1`timetoMaturity`assetType`datasource`clearRate, 
                        [SYMBOL, TIMESTAMP,DECIMAL32(3),DECIMAL32(3),DECIMAL32(3),DECIMAL32(3),DECIMAL32(3),DECIMAL32(3),DOUBLE,INT,INT,STRING])
assetType=[0,1,2]
fitMethod=[<piecewiseLinFit(timetoMaturity, midyield1, 10)>,
            <nss(timetoMaturity,bidyield1,"ns")>,
            <piecewiseLinFit(timetoMaturity, askyield1, 5)>]

modelOutput=table(1:0, `time`assetType`dataSource`clearRate`model,
                       [TIMESTAMP,INT,INT,SYMBOL,BLOB])
predictOutput=table(1:0, `time`assetType`dataSource`clearRate`x`y,[TIMESTAMP,INT,INT,SYMBOL,DOUBLE,DOUBLE])

engine = createYieldCurveEngine(name="test", dummyTable=dummyTable,assetType=assetType,fitMethod=fitMethod,
                                keyColumn=`assetType`dataSource`clearRate, modelOutput=modelOutput,
                                frequency=10,predictInputColumn=`timetoMaturity,predictTimeColumn=`sendingtime, 
                                predictOutput=predictOutput,fitAfterPredict=false)
                                
data = table(take(`a`b`c, 30) as  symbol, take(now(), 30) as time, decimal32(rand(10.0, 30),3) as p1,  decimal32(rand(10.0, 30),3) as p2,  decimal32(rand(10.0, 30),3) as p3, decimal32(rand(10.0, 30),3) as p4,  decimal32(rand(10.0, 30),3) as p5,  decimal32(rand(10.0, 30),3) as p6, (rand(10.0, 30)+10).sort() as timetoMaturity, take(0 1 2, 30) as assetType, take([1], 30) as datasource, take("1", 30) as clearRate)
engine.append!(data)                                

Use the appendForPrediction function to add data to the predictOutput table and retrieve the prediction results.

data = table(take(`a`b`c, 30) as  symbol, take(now(), 30) as time, decimal32(rand(10.0, 30),3) as p1,  decimal32(rand(10.0, 30),3) as p2,  decimal32(rand(10.0, 30),3) as p3, decimal32(rand(10.0, 30),3) as p4,  decimal32(rand(10.0, 30),3) as p5,  decimal32(rand(10.0, 30),3) as p6, (rand(10.0, 30)+10).sort() as timetoMaturity, take(0 1 2, 30) as assetType, take([1], 30) as datasource, take("1", 30) as clearRate)
appendForPrediction(engine, data) 
//Output: 30   

Related Function: createYieldCurveEngine