WAvelet System Prediction [Jiang, Z., Sharma, A., & Johnson, F. (2020). Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling. Water Resources Research, 56(3), e2019WR026962.]
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Updated
Aug 4, 2024 - R
WAvelet System Prediction [Jiang, Z., Sharma, A., & Johnson, F. (2020). Refining Predictor Spectral Representation Using Wavelet Theory for Improved Natural System Modeling. Water Resources Research, 56(3), e2019WR026962.]
The importance of converting relative to absolute abundance in the context of microbial ecology: Introducing the user-friendly DspikeIn R package
Geographically disaggregated data on low carbon technology deployment, electricity demand, meter density, and network infrastructure across Great Britain. Arranged at an LSOA level (~600 households). R scripts to generate and process this data.
z(log) transformation for laboratory values
PICAFlow: a complete R workflow dedicated to flow/mass cytometry data, from data pre-processing to deep and comprehensive analysis.
Ratio-of-Uniforms Simulation with Transformation.
This package intends to convert categorical features into numerical ones. This will help in employing algorithms and methods that only accept numerical data as input. The main motivation for writing this package is to use it in clustering assignments. https://ranibasna.github.io/NumericalTransformation/
This lab contains my first lab for data analysis and predictive modeling. This lab involves visualizing the data in multiple different ways.
trying to predict BAE system closing stock price vs the actual price
Sammenlikning av to utvalg, variansanalyse og forsøksplanlegging. Bivariat normalfordeling, korrelasjon og enkel regresjon. Innføring i ikke parametriske og Bayesianske metoder. Eksempler fra ulike anvendelsesområder blir gitt. Utvalgte emner fra sannsynlighetsregning blir også dekket, transformasjon av tilfeldige variable, momentgenerende funks…
Contains the second lab for data analysis and predictive modeling. Which involves cleaning a data set involving a candy company
This study develops a new clustering method for high-dimensional zero-inflated time-series data by proposing a similarity measure based on Thick Pen Transformation. Two real data set considered were step count data and newly confirmed COVID-19 case data.
R Package for Aligned Rank Transform for Nonparametric Factorial ANOVAs
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