如何使用Spark Scala从GeneralizedLinearRegressionModel计算pValue

import org.apache.spark.ml.regression.GeneralizedLinearRegressionModel
import org.apache.spark.ml.linalg.DenseVector
import org.apache.spark.ml.stat.ChiSquareTest

val coefficients: DenseVector = model.coefficients
val standardErrors: DenseVector = model.summary.coefficientStandardErrors

val numFeatures: Int = coefficients.size
val tValues: DenseVector = coefficients.toArray.zip(standardErrors.toArray).map {
  case (coefficient, standardError) => coefficient / standardError
}
val pValues: DenseVector = ChiSquareTest.test(tValues, numFeatures).pValues

println("pValues: " + pValues)