Operators: com.teracloud.streams.timeseries 7.0.0
Operators
- ARIMA2
- The ARIMA2 operator implements the autoregressive integrated moving average (ARIMA) modeling algorithm.
- AnomalyDetector
- The AnomalyDetector operator can detect anomalous subsequences in an incoming data stream.
- AutoForecaster2
- The AutoForecaster2 operator is a forecasting operator, which detects the algorithm that best suits the input time series data in real time and forecasts future time series.
- BATS
- The BATS operator is a forecasting operator, which can be used to do long-term forecasting of regular time series with complex seasonality by using the BATS algorithms.
- BoundedAnomalyDetector
- The BoundedAnomalyDetector operator detects anomalys (outliers) in a timeseries.
- CrossCorrelate2
- In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
- CrossCorrelateMulti
- In signal processing, cross-correlation is a measure of similarity of two time series as a function of a time-lag applied to one of them.
- DSPFilter2
- The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
- DSPFilterFinite
- The Digital Signal Processing (DSP) filter operator performs a digital filtering operation on an input time series.
- DWT2
- The DWT2 operator applies a discrete wavelet transform (DWT) on a vector time series.
- Distribution
- The Distribution operator calculates the quartile distribution for an input time series.
- FFT
- The FFT operator applies a transformation of a time series from time domain into frequency domain.
- FMPFilter
- The FMPFilter operator is an adaptive faded-memory polynomial filter.
- FunctionEvaluator
- The FunctionEvaluator operator applies a function to each value in a time series.
- GAMLearner
- The GAMLearner operator applies the generalized additive model (GAM) algorithm to categorical or continuous time series data.
- GAMScorer
- The GAMScorer operator applies a generalized additive model to score the input time series values.
- GMM
- The GMM operator uses a Gaussian mixture model to estimate the probability density function (a smoothed histogram) of a time series.
- Generator
- The Generator operator generates a sine, triangular, sawtooth, or a pulse train representation of a time series.
- HoltWinters2
- The HoltWinters2 operator is a forecasting operator, which uses the Holt-Winters algorithm to do long-term forecasting.
- HoltWinters3
- The HoltWinters3 operator is a forecasting operator, which can be used to do long-term forecasting of seasonal regular time series by using different variants of the Holt-Winters algorithms.
- IncrementalInterpolate
- The IncrementalInterpolate operator calculates missing values in a time series.
- KMeansClustering
- Cluster analysis is a popular technique used to find natural grouping of a set of objects.
- Kalman
- The Kalman operator runs an adaptive filter on a time series and can used for tracking, smoothing, adaptation.
- LPC
- The Linear Predictive Coding (LPC) operator uses an autoregressive (AR) model to predict values in a time series.
- Normalize
- The Normalize operator incrementally estimates the means and variance and can normalize the time series to zero means and unit variance.
- PSAX
- The PSAX operator is capable of providing a symbolic representation of real-valued time series data.
- RLSFilter
- The Recursive Least Squares (RLS) is linear regression estimation algorithm that learns to predict a target time series, given inputs.
- ReSample
- The ReSample operator changes the sampling rate of a time series.
- STD2
- The Seasonal Trend Decomposition (STD) operator uses the Loess algorithm to decompose an input time series into three components: the season, the trend and the residuals.
- TSWindowing
- The TSWindowing operator can be used to isolate a portion of the signal in a specified duration.
- VAR2
- The VAR2 operator tracks data movement and predicts the next expected time series by using a multivariate autoregressive model.