Lets-Plot-Kotlin/org.jetbrains.letsPlot/Stat/smooth

smooth

class smooth(val method: String? = null, val n: Int? = null, val level: Number? = null, val se: Boolean? = null, val span: Number? = null, val deg: Int? = null, val seed: Long? = null, val maxN: Int? = null, val mapping: SmoothStatMapping.() -> Unit = {}) : StatOptions, SmoothStatParameters

Constructors

smooth

constructor(method: String? = null, n: Int? = null, level: Number? = null, se: Boolean? = null, span: Number? = null, deg: Int? = null, seed: Long? = null, maxN: Int? = null, mapping: SmoothStatMapping.() -> Unit = {})

Properties

deg

open override val deg: Int? = null

Degree of polynomial for linear regression model.

kind

val kind: StatKind

level

open override val level: Number? = null

Level of confidence interval to use.

mapping

val mapping: Options

maxN

open override val maxN: Int? = null

Maximum number of data-points for LOESS method. If this quantity exceeded random sampling is applied to data.

method

open override val method: String? = null

Smoothing method: lm (Linear Model) or loess (Locally Estimated Scatterplot Smoothing).

open override val n: Int? = null

Number of points to evaluate smoother at.

parameters

open override val parameters: Options

open override val se: Boolean? = null

To display confidence interval around smooth.

seed

open override val seed: Long? = null

Random seed for LOESS sampling.

span

open override val span: Number? = null

The fraction of source points closest to the current point is taken into account for computing a least-squares regression. A sensible value is usually 0.25 to 0.5.