public class DoubleExponentialSmoothing extends AbstractExponentialSmoothing
When smoothing parameters are smaller more weights are added to the observations from distant past - it makes it model more robust.
Equations:
| Modifier and Type | Class and Description |
|---|---|
static class |
DoubleExponentialSmoothing.Optimizer |
static class |
DoubleExponentialSmoothing.State |
TimeSeriesModel.TimestampComparator| Modifier and Type | Field and Description |
|---|---|
static double |
DEFAULT_LEVEL_SMOOTHING |
static double |
DEFAULT_TREND_SMOOTHING |
static double |
MAX_LEVEL_TREND_SMOOTHING |
static double |
MIN_LEVEL_TREND_SMOOTHING |
lastTimestamp, metricContext| Modifier and Type | Method and Description |
|---|---|
protected double |
calculatePrediction(long nAhead,
Long learnTimestamp) |
static DoubleExponentialSmoothing |
createCustom(double levelSmoothing,
double trendSmoothing,
MetricContext metricContext) |
static DoubleExponentialSmoothing |
createDefault() |
static DoubleExponentialSmoothing |
createWithMetric(MetricContext metricContext) |
static DoubleExponentialSmoothing |
createWithSmoothingParams(double levelSmoothing,
double trendSmoothing) |
protected DoubleExponentialSmoothing.State |
initState(List<DataPoint> initData) |
int |
minimumInitSize() |
String |
name() |
int |
numberOfParams() |
static DoubleExponentialSmoothing.Optimizer |
optimizer() |
static DoubleExponentialSmoothing.Optimizer |
optimizer(MetricContext metricContext) |
protected DoubleExponentialSmoothing.State |
state() |
String |
toString() |
protected void |
updateState(DataPoint dataPoint) |
forecast, forecast, init, initStatistics, lastTimestamp, learn, learn, runStatisticspublic static final double DEFAULT_LEVEL_SMOOTHING
public static final double DEFAULT_TREND_SMOOTHING
public static final double MIN_LEVEL_TREND_SMOOTHING
public static final double MAX_LEVEL_TREND_SMOOTHING
public static DoubleExponentialSmoothing createDefault()
public static DoubleExponentialSmoothing createWithMetric(MetricContext metricContext)
public static DoubleExponentialSmoothing createWithSmoothingParams(double levelSmoothing, double trendSmoothing)
public static DoubleExponentialSmoothing createCustom(double levelSmoothing, double trendSmoothing, MetricContext metricContext)
public String name()
public int numberOfParams()
public int minimumInitSize()
protected DoubleExponentialSmoothing.State initState(List<DataPoint> initData)
initState in class AbstractExponentialSmoothingprotected DoubleExponentialSmoothing.State state()
state in class AbstractExponentialSmoothingprotected void updateState(DataPoint dataPoint)
updateState in class AbstractExponentialSmoothingprotected double calculatePrediction(long nAhead,
Long learnTimestamp)
calculatePrediction in class AbstractExponentialSmoothingpublic static DoubleExponentialSmoothing.Optimizer optimizer()
public static DoubleExponentialSmoothing.Optimizer optimizer(MetricContext metricContext)
Copyright © 2015–2016 Red Hat, Inc.. All rights reserved.