R-universe search: exports:snr

Showing 6 of total 6 results (show query)

sgibb

MALDIquant:Quantitative Analysis of Mass Spectrometry Data

A complete analysis pipeline for matrix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) and other two-dimensional mass spectrometry data. In addition to commonly used plotting and processing methods it includes distinctive features, namely baseline subtraction methods such as morphological filters (TopHat) or the statistics-sensitive non-linear iterative peak-clipping algorithm (SNIP), peak alignment using warping functions, handling of replicated measurements as well as allowing spectra with different resolutions.

Maintained by Sebastian Gibb. Last updated 7 months ago.

maldi maldi-ims maldi-tof-ms mass-spectrometry

62 stars 11.06 score 180 scripts 44 dependents

bioc

beadarray:Quality assessment and low-level analysis for Illumina BeadArray data

The package is able to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided.

Maintained by Mark Dunning. Last updated 5 months ago.

microarray onechannel qualitycontrol preprocessing

7.88 score 70 scripts 4 dependents

yuimaproject

yuima:The YUIMA Project Package for SDEs

Simulation and Inference for SDEs and Other Stochastic Processes.

Maintained by Stefano M. Iacus. Last updated 10 hours ago.

openblas cpp

9 stars 7.02 score 92 scripts 2 dependents

christianroever

bspec:Bayesian Spectral Inference

Bayesian inference on the (discrete) power spectrum of time series.

Maintained by Christian Roever. Last updated 3 years ago.

2.71 score 86 scripts 2 dependents

cran

dSTEM:Multiple Testing of Local Extrema for Detection of Change Points

Simultaneously detect the number and locations of change points in piecewise linear models under stationary Gaussian noise allowing autocorrelated random noise. The core idea is to transform the problem of detecting change points into the detection of local extrema (local maxima and local minima)through kernel smoothing and differentiation of the data sequence, see Cheng et al. (2020) <doi:10.1214/20-EJS1751>. A low-computational and fast algorithm call 'dSTEM' is introduced to detect change points based on the 'STEM' algorithm in D. Cheng and A. Schwartzman (2017) <doi:10.1214/16-AOS1458>.

Maintained by Zhibing He. Last updated 2 years ago.

1.00 score

cran

assist:A Suite of R Functions Implementing Spline Smoothing Techniques

Fit various smoothing spline models. Includes an ssr() function for smoothing spline regression, an nnr() function for nonparametric nonlinear regression, an snr() function for semiparametric nonlinear regression, an slm() function for semiparametric linear mixed-effects models, and an snm() function for semiparametric nonlinear mixed-effects models. See Wang (2011) <doi:10.1201/b10954> for an overview.

Maintained by Yuedong Wang. Last updated 2 years ago.

fortran openblas

1.00 score