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ipft (version 0.2.2)

Indoor Positioning Fingerprinting Toolset

Description

Algorithms and utility functions for indoor positioning using fingerprinting techniques. These functions are designed for manipulation of RSSI (Received Signal Strength Intensity) data sets, estimation of positions,comparison of the performance of different models, and graphical visualization of data. Machine learning algorithms and methods such as k-nearest neighbors or probabilistic fingerprinting are implemented in this package to perform analysis and estimations over RSSI data sets.

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Version

Install

install.packages('ipft')

Monthly Downloads

188

Version

0.2.2

License

GPL (>= 2)

Maintainer

Emilio Sansano

Last Published

February 21st, 2017

Functions in ipft (0.2.2)

ipfKnn

This function implements the k-nearest neighbors algorithm
ipfPlotEst

Plots the estimated locations
ipfPlotEcdf

Plots the cumulative distribution function of the estimated error
ipfPlotPdf

Plots the probability density function of the estimated error
ipfEstimate

This function estimates the location of the test observations
ipfProb

This function implements a probabilistic algorithm
ipfGroup

Creates groups based on the specified parameters
ipfPlotLoc

Plots the spatial location of the observations
ipfCluster

Creates clusters using the specified method
ipfDist

Distance function
ipfTransform

Transform function
ipftrain

Indoor localization training data set to test Indoor Positioning System that
ipftest

Indoor localization test data set to test Indoor Positioning System that