Commands model:arima/train

[ALPHA] Creates Autoregressive Integrated Moving Average (ARIMA) Model from the specified time series values.

POST /v1/commands/

GET /v1/commands/:id

Request

Route

POST /v1/commands/

Body

name:

model:arima/train

arguments:

model : Model

<Missing Description>

timeseries_values : list

List of time series values.

p : int32

Autoregressive order

d : int32

Differencing order

q : int32

Moving average order

include_intercept : bool (default=True)

If true, the model is fit with an intercept. Default is True

method : unicode (default=css-cgd)

Objective function and optimization method. Current options are: ‘css-bobyqa’ and ‘css-cgd’. Both optimize the log likelihood in terms of the conditional sum of squares. The first uses BOBYQA for optimization, while the second uses conjugate gradient descent. Default is ‘css-cgd’.

user_init_params : list (default=None)

A set of user provided initial parameters for optimization. If the list is empty (default), initialized using Hannan-Rissanen algorithm. If provided, order of parameter should be: intercept term, AR parameters (in increasing order of lag), MA parameters (in increasing order of lag)

Headers

Authorization: test_api_key_1
Content-type: application/json

Description

Given a time series, fits an non-seasonal Autoregressive Integrated Moving Average (ARIMA) model of order (p, d, q) where p represents the autoregression terms, d represents the order of differencing, and q represents the moving average error terms. If includeIntercept is true, the model is fitted with an intercept.

Response

Status

200 OK

Body

Returns information about the command. See the Response Body for Get Command here below. It is the same.

GET /v1/commands/:id

Request

Route

GET /v1/commands/18

Body

(None)

Headers

Authorization: test_api_key_1
Content-type: application/json

Response

Status

200 OK

Body

dict

Array of coefficients (intercept, AR, MA, with increasing degrees).