pyPhenology.models.Linear

class pyPhenology.models.Linear(parameters={})

Linear Regression Model

A 2 parameter regression model with \(DOY\) as the response variable.

\[DOY = \beta_{1} + \beta_{2}T_{mean}\]

where \(T_{mean}\) is the mean temperature of the time period specified. By default it is set to model spring phenology (with mean temperature of Jan. 1 - March 31). This can also be used for fall phenology by setting the time parameters to the late summer/fall season.

Parameters:

intercept : int | float

\(\beta_{1}\), intercept of the model

default : (-67,298)

slope : int | float

\(\beta_{1}\), Slope of the model

default : (-25,25)

time_start : int

Start doy for the season of interest

default : 1 (Jan 1)

time_length : int

The length of the season in days

default : 90

__init__(parameters={})

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([parameters])	Initialize self.
fit(observations, predictors[, …])	Estimate the parameters of a model
get_params()	Get the fitted parameters
predict([to_predict, predictors])	Make predictions
save_params(filename[, overwrite])	Save the parameters for a model
score([metric, doy_observed, to_predict, …])	Evaluate a prediction given observed doy values