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widals (version 0.6.2)

Weighting by Inverse Distance with Adaptive Least Squares

Description

Computationally easy modeling, interpolation, forecasting of massive temporal-spacial data.

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Version

Install

install.packages('widals')

Monthly Downloads

195

Version

0.6.2

License

GPL (>= 2)

Maintainer

Dave Zes

Last Published

March 24th, 2025

Functions in widals (0.6.2)

create.rm.ndx.ls

Cross-Validation Indices
applystnd.Hst.ls

Standardize Space-Time Covariates with Existing Object
fuse.Hst.ls

Merge Contemporaneous Space-Time Covariates
unif.mh

Local Search Function
load.Hst.ls.2Zs

Load Observations into Space-Time Covariates
unload.Hst.ls

Convert a Space-Time Covariate into Data
stnd.Ht

Standardize Temporal Covariates
subsetsites.Hst.ls

Site-Wise Extract Space-Time Covariates
fun.load

Stochastic Search Helper Functions
widals.snow

Fit WIDALS
distance

Spacial Distance
crispify

Observation-Space Stochastic Correction
stnd.Hs

Standardize Spacial Covariates
stnd.Hst.ls

Standardize Space-Time Covariates
widals-package

Weighting by Inverse Distance with Adaptive Least Squares for Massive Space-Time Data
widals.predict

WIDALS Interpolation
Hals.snow

Fit ALS
O3

California Ozone
Hals.ses

Effective Standard Errors
H.Earth.solar

Solar Radiation
applystnd.Hs

Standardize Spacial Covariates with Existing Object
H.als.b

Adaptive Least Squares
Z.clean.up

Clean Data
Hals.fastcv.snow

ALS Spacial Cross-Validation
Hst.sumup

Create Covariance Matrix
MSS.snow

Metaheuristic Stochastic Search
dlog.norm

Local Search Function
load.Hst.ls.Z

Load Observations into Space-Time Covariates
rm.cols.Hst.ls

Remove Space-Time Covariates from Model