pyPhenology.models.Naive

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

A naive model of the spatially interpolated mean

This is the mean doy for an event adjusted for latitude, essentially a 2 parameter regression model with \(DOY\) as the response variable.

\[DOY = \beta_{1} + \beta_{2}Latitude\]

This model requires only a latitude column in the predictors for each unique site_id

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)

__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