case class Glm(y: DVD, Xmat: DMD, colNames: Seq[String], fam: GlmFamily, addIntercept: Boolean = true, its: Int = 50) extends Model with Product with Serializable
Generalised linear regression modelling
- y
Vector of responses
- Xmat
Covariate matrix
- colNames
List of covariate names
- fam
Observation model. eg. LogisticGlm or PoissonGlm
- addIntercept
Add an intercept term to the covariate matrix?
- its
Max iterations for the IRLS algorithm (default 50)
- returns
An object of type Glm with many useful methods providing information about the regression fit, including .coefficients, .p and .summary
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Instance Constructors
- new Glm(y: DVD, Xmat: DMD, colNames: Seq[String], fam: GlmFamily, addIntercept: Boolean = true, its: Int = 50)
- y
Vector of responses
- Xmat
Covariate matrix
- colNames
List of covariate names
- fam
Observation model. eg. LogisticGlm or PoissonGlm
- addIntercept
Add an intercept term to the covariate matrix?
- its
Max iterations for the IRLS algorithm (default 50)
Value Members
- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- final def ==(arg0: Any): Boolean
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- val X: DMD
Design matrix (including the intercept column, if required)
- val Xmat: DMD
- val addIntercept: Boolean
- final def asInstanceOf[T0]: T0
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- def clone(): AnyRef
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- @throws(classOf[java.lang.CloneNotSupportedException]) @IntrinsicCandidate() @native()
- val coefficients: DVD
Fitted regression coefficients
- val colNames: Seq[String]
- lazy val df: Int
Degrees of freedom
- final def eq(arg0: AnyRef): Boolean
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- val fam: GlmFamily
- lazy val fitted: DVD
- final def getClass(): Class[_ <: AnyRef]
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- @IntrinsicCandidate() @native()
- val irls: (DVD, DMD, DMD)
Tuple containing results of running the IRLS algorithm - not for general use
- final def isInstanceOf[T0]: Boolean
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- val its: Int
- lazy val n: Int
Number of observations
- val names: Seq[String]
Sequence of variable names (including the intercept)
- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- lazy val p: DenseVector[Double]
p-values for the regression coefficients
- def plots: Figure
- lazy val pp: Int
Number of variables (including the intercept)
- def predict(newX: DMD = Xmat, response: Boolean = false): PredictGlm
Predictions for a new matrix of covariates
Predictions for a new matrix of covariates
- newX
New matrix of covariates
- response
Fitted values on the scale of the response?
- returns
Prediction object
- def productElementNames: Iterator[String]
- Definition Classes
- Product
- val q: DMD
Final Q-matrix from the IRLS algorithm
- val r: DMD
Final R-matrix from the IRLS algorithm
- lazy val ri: DenseMatrix[Double]
Inverse of the final R-matrix
- lazy val se: DenseVector[Double]
Standard errors for the regression coefficients
- def summary: Unit
Prints a human-readable regression summary to the console
- final def synchronized[T0](arg0: => T0): T0
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- final def wait(arg0: Long, arg1: Int): Unit
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- val y: DVD
- lazy val z: DenseVector[Double]
z-statistics for the regression coefficients
Deprecated Value Members
- def finalize(): Unit
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- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated
(Since version 9)