Introduction

This document describes the use of the functions implemented in TimeSeries.OBeu package in OpenCPU environment, after installing OpenCPU and TimeSeries.OBeu package on your OpenCPU server address(/ocpu/test).

How to use functions

Go to: yourserver/ocpu/test
Type to the endpoint:

 ../library/ {name of the library} /R/ {function}

If you want to see the function parameters you should:
- Select Method: Get
To run a function you should:
- Select Method: Post
Then you can click on Ajax Request.

OpenCPU and TimeSeries.OBeu

ts.analysis

In this example we will use ts.analysis function that returns in a single call a json string or a list with the following components:

*`ts.analysis`* components
Component	Output	Description
acf.parameters	acf acf.lag confidence.interval.up confidence.interval.low	ACF values of the input time series Lags at which the acf is estimated Upper limit of the confidence interval Lower limit of the confidence interval
pacf.parameters	pacf pacf.lag confidence.interval.up confidence.interval.low	PACF values of the input time series Lags at which the pacf is estimated Upper limit of the confidence interval Lower limit of the confidence interval
acf.residuals.parameters	acf.res acf.res.lag confidence.interval.up confidence.interval.low	ACF values of the model residuals Lags at which the acf is estimated of the model residuals Upper limit of the confidence interval Lower limit of the confidence interval
pacf.residuals.parameters	pacf.res pacf.res.lag confidence.interval.up confidence.interval.low	Pacf values of the model residuals Lags at which the pacf is estimated of the model residuals Upper limit of confidence interval Lower limit of confidence interval
stl.plot	trend trend.ci.up trend.ci.low seasonal remainder time	Trend component Up limit for trend component Low limit for trend component Seasonal component Remainder component Time of the series was sampled
stl.general	stl.degree degfr degfr.fitted fitted	Degree of fit Effective degrees of freedom Fitted degrees of freedom Model’s fitted values
residuals	residuals	Residuals of the model
compare	arima.order arima.coef arima.coef.se covariance.coef resid.variance not.used.obs used.obs loglik aic bic gcv aicc	Arima order AR, MA and regression coefficients Standard error of the coefficients Variance of the coefficients Residuals variance Number of not used observations Used observations Maximized log-likelihood, AIC value BIC value Generalized cross-validation statistic Second-order AIC
forecasts	ts.model data_year data predict_time predict_values up80 low80 up95 low95	A string indicating the arima orders Time of time series data Time series values Time of the predicted values Predicted values Upper 80% confidence limit Lower 80% confidence limit Upper 95% confidence limit Lower 95% confidence limit

Select library and function

Go to: yourserver/ocpu/test
Copy and paste the following function to the endpoint

../library/TimeSeries.OBeu/R/ts.analysis
# library/ {name of the library} /R/ {function}

Select Method: Post

Adding parameters parameters

Click add parameters every time you want to add a new parameters and values.

Define the input data:
- Param Name: tsdata
- Param Value: e.g. Athens_executed_ts
Define the prediction steps parameter:
- Param Name: prediction.steps
- Param Value: 2

You add likewise x.order parameter to fit a specific arima order, see TimeSeries.OBeu reference manual for further details.

Using TimeSeries.OBeu with OpenCPU

Introduction

How to use functions

OpenCPU and TimeSeries.OBeu

ts.analysis

Select library and function

Adding parameters parameters

Results

Further Details

Github

Contents