Degree |
For using the API to run regressions against your energy-usage data.
Classes| Class | Description | |
|---|---|---|
 | BaseloadRegressionComponent | Contains details of the baseload component (non-weather-dependent energy usage) in a regression. |
| DegreeDaysRegressionComponent | Contains details of a heating or cooling component in a regression, with the base temperature and degree days used, as well as the usual coefficient and stats. |
| ExtraPredictorSpec | Defines an extra predictor in terms of its PredictorType and ExpectedCorrelation, to help the API test and rank regressions that include data for that extra predictor. |
| ExtraRegressionComponent | Contains details of an extra-predictor component in a regression. |
| InputData | Defines the energy data (and any extra-predictor data) that the API should run regressions against. |
| InputPeriod | Defines a dated period with its energy usage and any extra-predictor figures. |
| Regression | Contains details of a regression model that the API calculated using the InputData you provided and, typically, HDD and/or CDD as well. |
| RegressionApi | Provides easy, type-safe access to the API's regression-related operations. |
| RegressionComponent | Contains details of a regression component e.g. the baseload (b*days) or the heating (h*HDD) component in a regression like E = b*days + h*HDD. |
| RegressionRequest | Defines a request for the API to test regressions against the specified energy data (InputData) using degree days from the specified Location. |
| RegressionResponse | Contains a selection of the regressions that the API tested against your RegressionRequest, with the Regression that gave the best statistical fit listed first. |
| RegressionSpec | Defines a specification of a regression in terms of its HDD and/or CDD base temperature(s) and any extra predictors to be included. |
| RegressionTestPlan | Defines how the API should test regressions against the InputData you provide it. |
Structures| Structure | Description | |
|---|---|---|
 | DayNormalization | Defines the day normalization used in the regression process – an important consideration when periods of energy usage cover different lengths of time. |
| ExpectedCorrelation | Defines how an extra predictor's figures are expected to correlate with energy usage (whether larger predictor numbers lead to larger or smaller energy usage). |
| PredictorType | Defines an extra predictor's figures as being cumulative (increasing with time and naturally larger over longer periods) or average (normalized such that the length of the period has no effect). |
| RegressionTag | Tags that the API adds to Regression objects to indicate why it included them in a RegressionResponse. |
RemarksIf you are new to this package, we suggest you start by looking at RegressionApi.