pwlfPredict

pwlfPredict(model, X, [beta], [breaks])

model is a dictionary returned by piecewiseLinFit.

X is a numeric vector indicating the x locations to predict the output of the fitted continuous piecewise linear function. NULL value is not allowed.

beta (optional) is a numeric vector indicating the model parameters for the continuous piecewise linear fit. NULL value is not allowed.

breaks (optional) is a numeric vector indicating the x locations where each line segment terminates. These are referred to as breakpoints for each line segment. NULL value is not allowed.

Evaluate the fitted continuous piecewise linear function at untested points.

Return value: A floating-point vector.

def linspace(start, end, num, endpoint=true){
	if(endpoint) return end$DOUBLE\(num-1), start + end$DOUBLE\(num-1)*0..(num-1)
	else return start + end$DOUBLE\(num-1)*0..(num-1)	
}
X = linspace(0.0, 1.0, 10)[1]
Y = [0.41703981, 0.80028691, 0.12593987, 0.58373723, 0.77572962, 0.41156172, 0.72300284, 0.32559528, 0.21812564, 0.41776427]
// Fit a continuous piecewise linear function
model = piecewiseLinFit(X, Y, 3)
// Pass x locations
xHat = linspace(0.0, 1.0, 20)[1]
// Evaluate xHat using the model
pwlfPredict(model, xHat)

// output: [0.593305499919518 0.524360777381737 0.455416054843957 0.386471332306177 0.317526609768396 0.368043438179296 0.529813781212159 0.691584124245021 0.69295837868457  0.655502915538459 0.618047452392347 0.580591989246236 0.543136526100125 0.505681062954014 0.468225599807903 0.430770136661792 0.393314673515681 0.35585921036957  0.318403747223459 0.280948284077348]

Related function: piecewiseLinFit