Polypred: Difference between revisions

Latest revision as of 13:53, 6 March 2013

Make predictions for partial least squares regression models with polynomial inner relations.

ypred = polypred(x,b,p,q,w,lv)

POLYPRED uses parameters created by the routine POLYPLS to make predictions from a new x-block matrix of predictor variables x.

Note: It is important that the scaling of the new data x is the same as that used to create the model parameters in POLYPLS.

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 ===Purpose===
 Make predictions for partial least squares regression models with polynomial inner relations.
 ===Synopsis===
 :ypred = polypred(x,b,p,q,w,lv)
 ===Description===
-POLYPRED uses parameters created by the routine POLYPLS to make predictions from a new x-block matrix of predictor variables x. Inputs are b a matrix of polynomial coefficients for the inner relationship, p the x-block latent variable loadings, q the y-block variable loadings, w the x-block latent variable weights, and the number of latent variables lv.
+POLYPRED uses parameters created by the routine POLYPLS to make predictions from a new x-block matrix of predictor variables x.
 Note: It is important that the scaling of the new data x is the same as that used to create the model parameters in POLYPLS.
+====Inputs====
+* '''b''' = a matrix of polynomial coefficients for the inner relationship,
+* '''p''' = the x-block latent variable loadings,
+* '''q''' = the y-block variable loadings,
+* '''w''' = the x-block latent variable weights,
+* '''lv''' = the number of latent variables lv.
+====Outputs====
+* '''ypred''' = y-block predictions.
 ===See Also===
 [[lwrxy]], [[polypls]], [[pls]]