Showing 56 of total 56 results (show query)
ropensci
medrxivr:Access and Search MedRxiv and BioRxiv Preprint Data
An increasingly important source of health-related bibliographic content are preprints - preliminary versions of research articles that have yet to undergo peer review. The two preprint repositories most relevant to health-related sciences are medRxiv <https://www.medrxiv.org/> and bioRxiv <https://www.biorxiv.org/>, both of which are operated by the Cold Spring Harbor Laboratory. 'medrxivr' provides programmatic access to the 'Cold Spring Harbour Laboratory (CSHL)' API <https://api.biorxiv.org/>, allowing users to easily download medRxiv and bioRxiv preprint metadata (e.g. title, abstract, publication date, author list, etc) into R. 'medrxivr' also provides functions to search the downloaded preprint records using regular expressions and Boolean logic, as well as helper functions that allow users to export their search results to a .BIB file for easy import to a reference manager and to download the full-text PDFs of preprints matching their search criteria.
Maintained by Yaoxiang Li. Last updated 1 months ago.
bibliographic-databasebiorxivevidence-synthesismedrxiv-datapeer-reviewedpreprint-recordssystematic-reviews
16.9 match 56 stars 7.17 score 44 scripts
arnaudgallou
plume:A Simple Author Handler for Scientific Writing
Handles and formats author information in scientific writing in 'R Markdown' and 'Quarto'. 'plume' provides easy-to-use and flexible tools for injecting author metadata in 'YAML' headers as well as generating author and contribution lists (among others) as strings from tabular data.
Maintained by Arnaud Gallou. Last updated 30 days ago.
authorscontributioncontributionslistlistsmarkdownpaperpreprintquartoroleroles
11.0 match 21 stars 6.84 score 15 scripts
lazappi
doilinker:Link Preprints And Publications By DOI
Links preprints to publications using the method described in Cabanac G, Oikonomidi T, Boutron I. "Day-to-day discovery of preprint-publication links". Scientometrics. 2021;1–20. DOI: 10.1007/s11192-021-03900-7.
Maintained by Luke Zappia. Last updated 1 years ago.
17.2 match 5 stars 3.40 score 3 scripts
stephenturner
biorecap:Retrieve and summarize bioRxiv and medRxiv preprints with a local LLM using ollama
Retrieve and summarize bioRxiv and medRxiv preprints with a local LLM using ollama.
Maintained by Stephen Turner. Last updated 6 months ago.
12.8 match 64 stars 4.20 score 5 scripts
alexanderhenzi
isodistrreg:Isotonic Distributional Regression (IDR)
Distributional regression under stochastic order restrictions for numeric and binary response variables and partially ordered covariates. See Henzi, Ziegel, Gneiting (2021) <doi:10.1111/rssb.12450>.
Maintained by Alexander Henzi. Last updated 1 years ago.
3.3 match 15 stars 5.20 score 21 scripts
rfastofficial
Rfast2:A Collection of Efficient and Extremely Fast R Functions II
A collection of fast statistical and utility functions for data analysis. Functions for regression, maximum likelihood, column-wise statistics and many more have been included. C++ has been utilized to speed up the functions. References: Tsagris M., Papadakis M. (2018). Taking R to its limits: 70+ tips. PeerJ Preprints 6:e26605v1 <doi:10.7287/peerj.preprints.26605v1>.
Maintained by Manos Papadakis. Last updated 1 years ago.
0.8 match 38 stars 8.09 score 75 scripts 26 dependents
pascalkieslich
mousetrap:Process and Analyze Mouse-Tracking Data
Mouse-tracking, the analysis of mouse movements in computerized experiments, is a method that is becoming increasingly popular in the cognitive sciences. The mousetrap package offers functions for importing, preprocessing, analyzing, aggregating, and visualizing mouse-tracking data. An introduction into mouse-tracking analyses using mousetrap can be found in Wulff, Kieslich, Henninger, Haslbeck, & Schulte-Mecklenbeck (2023) <doi:10.31234/osf.io/v685r> (preprint: <https://osf.io/preprints/psyarxiv/v685r>).
Maintained by Pascal J. Kieslich. Last updated 1 years ago.
analysisclusteringmouse-trackingvisualizationcpp
0.8 match 46 stars 6.68 score 124 scriptsropensci
aRxiv:Interface to the arXiv API
An interface to the API for 'arXiv', a repository of electronic preprints for computer science, mathematics, physics, quantitative biology, quantitative finance, and statistics.
Maintained by Karl Broman. Last updated 1 years ago.
arxivarxiv-analyticsarxiv-apiarxiv-org
0.5 match 63 stars 6.97 score 74 scripts
frbcesab
rcompendium:Create a Package or Research Compendium Structure
Makes easier the creation of R package or research compendium (i.e. a predefined files/folders structure) so that users can focus on the code/analysis instead of wasting time organizing files. A full ready-to-work structure is set up with some additional features: version control, remote repository creation, CI/CD configuration (check package integrity under several OS, test code with 'testthat', and build and deploy website using 'pkgdown'). This package heavily relies on the R packages 'devtools' and 'usethis' and follows recommendations made by Wickham H. (2015) <ISBN:9781491910597> and Marwick B. et al. (2018) <doi:10.7287/peerj.preprints.3192v2>.
Maintained by Nicolas Casajus. Last updated 1 months ago.
reproducible-researchresearch-compendium
0.5 match 40 stars 6.72 score 22 scripts
nsaph-software
CRE:Interpretable Discovery and Inference of Heterogeneous Treatment Effects
Provides a new method for interpretable heterogeneous treatment effects characterization in terms of decision rules via an extensive exploration of heterogeneity patterns by an ensemble-of-trees approach, enforcing high stability in the discovery. It relies on a two-stage pseudo-outcome regression, and it is supported by theoretical convergence guarantees. Bargagli-Stoffi, F. J., Cadei, R., Lee, K., & Dominici, F. (2023) Causal rule ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment Effects. arXiv preprint <doi:10.48550/arXiv.2009.09036>.
Maintained by Falco Joannes Bargagli Stoffi. Last updated 5 months ago.
0.5 match 13 stars 6.41 score 11 scriptsnsaph-software
GPCERF:Gaussian Processes for Estimating Causal Exposure Response Curves
Provides a non-parametric Bayesian framework based on Gaussian process priors for estimating causal effects of a continuous exposure and detecting change points in the causal exposure response curves using observational data. Ren, B., Wu, X., Braun, D., Pillai, N., & Dominici, F.(2021). "Bayesian modeling for exposure response curve via gaussian processes: Causal effects of exposure to air pollution on health outcomes." arXiv preprint <doi:10.48550/arXiv.2105.03454>.
Maintained by Boyu Ren. Last updated 11 months ago.
0.5 match 9 stars 6.33 score 16 scripts
shaunpwilkinson
insect:Informatic Sequence Classification Trees
Provides tools for probabilistic taxon assignment with informatic sequence classification trees. See Wilkinson et al (2018) <doi:10.7287/peerj.preprints.26812v1>.
Maintained by Shaun Wilkinson. Last updated 4 years ago.
0.5 match 14 stars 5.80 score 91 scripts
brandmaier
reproducibleRchunks:Automated Reproducibility Checks for R Markdown Documents
Provide reproducible R chunks in R Markdown document that automatically check computational results for reproducibility. This is achieved by creating json files storing metadata about computational results. A comprehensive tutorial to the package is available as preprint by Brandmaier & Peikert (2024, <doi:10.31234/osf.io/3zjvf>).
Maintained by Andreas M. Brandmaier. Last updated 17 days ago.
0.5 match 25 stars 5.55 score 11 scripts
sehellmann
dynConfiR:Dynamic Models for Confidence and Response Time Distributions
Provides density functions for the joint distribution of choice, response time and confidence for discrete confidence judgments as well as functions for parameter fitting, prediction and simulation for various dynamical models of decision confidence. All models are explained in detail by Hellmann et al. (2023; Preprint available at <https://osf.io/9jfqr/>, published version: <doi:10.1037/rev0000411>). Implemented models are the dynaViTE model, dynWEV model, the 2DSD model (Pleskac & Busemeyer, 2010, <doi:10.1037/a0019737>), and various race models. C++ code for dynWEV and 2DSD is based on the 'rtdists' package by Henrik Singmann.
Maintained by Sebastian Hellmann. Last updated 17 hours ago.
0.5 match 3 stars 5.47 score 18 scripts
tslumley
DHBins:Hexmaps for NZ District Health Boards
Draws stylized choropleth maps -- hexagonal maps and triangular multiclass hex maps -- for New Zealand District Health Boards and Regional Council areas. These allow faceted, coloured displays of quantitative information for comparison across District Health Boards or Regional Councils. The preprint Lumley (2019) <arXiv:1912.04435> is based on the methods in this package.
Maintained by Thomas Lumley. Last updated 3 years ago.
0.5 match 3 stars 4.59 score 13 scripts
greifflab
immuneSIM:Tunable Simulation of B- And T-Cell Receptor Repertoires
Simulate full B-cell and T-cell receptor repertoires using an in silico recombination process that includes a wide variety of tunable parameters to introduce noise and biases. Additional post-simulation modification functions allow the user to implant motifs or codon biases as well as remodeling sequence similarity architecture. The output repertoires contain records of all relevant repertoire dimensions and can be analyzed using provided repertoire analysis functions. Preprint is available at bioRxiv (Weber et al., 2019 <doi:10.1101/759795>).
Maintained by Cédric R. Weber. Last updated 1 years ago.
0.5 match 37 stars 4.44 score 15 scripts
bioc
DepInfeR:Inferring tumor-specific cancer dependencies through integrating ex-vivo drug response assays and drug-protein profiling
DepInfeR integrates two experimentally accessible input data matrices: the drug sensitivity profiles of cancer cell lines or primary tumors ex-vivo (X), and the drug affinities of a set of proteins (Y), to infer a matrix of molecular protein dependencies of the cancers (ß). DepInfeR deconvolutes the protein inhibition effect on the viability phenotype by using regularized multivariate linear regression. It assigns a “dependence coefficient” to each protein and each sample, and therefore could be used to gain a causal and accurate understanding of functional consequences of genomic aberrations in a heterogeneous disease, as well as to guide the choice of pharmacological intervention for a specific cancer type, sub-type, or an individual patient. For more information, please read out preprint on bioRxiv: https://doi.org/10.1101/2022.01.11.475864.
Maintained by Junyan Lu. Last updated 5 months ago.
softwareregressionpharmacogeneticspharmacogenomicsfunctionalgenomics
0.5 match 1 stars 4.36 score 23 scripts
collinerickson
CGGP:Composite Grid Gaussian Processes
Run computer experiments using the adaptive composite grid algorithm with a Gaussian process model. The algorithm works best when running an experiment that can evaluate thousands of points from a deterministic computer simulation. This package is an implementation of a forthcoming paper by Plumlee, Erickson, Ankenman, et al. For a preprint of the paper, contact the maintainer of this package.
Maintained by Collin Erickson. Last updated 1 years ago.
0.5 match 2 stars 4.08 score 12 scripts
rtgodwin
oneinfl:Estimates OIPP and OIZTNB Regression Models
Estimates one-inflated positive Poisson (OIPP) and one-inflated zero-truncated negative binomial (OIZTNB) regression models. A suite of ancillary statistical tools are also provided, including: estimation of positive Poisson (PP) and zero-truncated negative binomial (ZTNB) models; marginal effects and their standard errors; diagnostic likelihood ratio and Wald tests; plotting; predicted counts and expected responses; and random variate generation. The models and tools, as well as four applications, are shown in Godwin, R. T. (2024). "One-inflated zero-truncated count regression models" arXiv preprint <arXiv:2402.02272>.
Maintained by Ryan T. Godwin. Last updated 2 months ago.
0.5 match 2 stars 3.78 score
ncsoft
promotionImpact:Analysis & Measurement of Promotion Effectiveness
Analysis and measurement of promotion effectiveness on a given target variable (e.g. daily sales). After converting promotion schedule into dummy or smoothed predictor variables, the package estimates the effects of these variables controlled for trend/periodicity/structural change using prophet by Taylor and Letham (2017) <doi:10.7287/peerj.preprints.3190v2> and some prespecified variables (e.g. start of a month).
Maintained by Nahyun Kim. Last updated 5 years ago.
0.5 match 47 stars 3.67 score 2 scripts
tobiaskley
forecastSNSTS:Forecasting for Stationary and Non-Stationary Time Series
Methods to compute linear h-step ahead prediction coefficients based on localised and iterated Yule-Walker estimates and empirical mean squared and absolute prediction errors for the resulting predictors. Also, functions to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time series, and to verify an assumption from Kley et al. (2017), Preprint <http://personal.lse.ac.uk/kley/forecastSNSTS.pdf>.
Maintained by Tobias Kley. Last updated 7 years ago.
0.5 match 5 stars 3.40 score 9 scripts
lukaswallrich
rsprite2:Identify Distributions that Match Reported Sample Parameters (SPRITE)
The SPRITE algorithm creates possible distributions of discrete responses based on reported sample parameters, such as mean, standard deviation and range (Heathers et al., 2018, <doi:10.7287/peerj.preprints.26968v1>). This package implements it, drawing heavily on the code for Nick Brown's 'rSPRITE' Shiny app <https://shiny.ieis.tue.nl/sprite/>. In addition, it supports the modeling of distributions based on multi-item (Likert-type) scales and the use of restrictions on the frequency of particular responses.
Maintained by Lukas Wallrich. Last updated 1 years ago.
0.5 match 2 stars 3.30 score 10 scripts
jmbh
fspe:Estimating the Number of Factors in EFA with Out-of-Sample Prediction Errors
Estimating the number of factors in Exploratory Factor Analysis (EFA) with out-of-sample prediction errors using a cross-validation scheme. Haslbeck & van Bork (Preprint) <https://psyarxiv.com/qktsd>.
Maintained by Jonas Haslbeck. Last updated 2 years ago.
0.5 match 1 stars 3.18 score 2 scripts 1 dependents
cran
prevtoinc:Prevalence to Incidence Calculations for Point-Prevalence Studies in a Nosocomial Setting
Functions to simulate point prevalence studies (PPSs) of healthcare-associated infections (HAIs) and to convert prevalence to incidence in steady state setups. Companion package to the preprint Willrich et al., From prevalence to incidence - a new approach in the hospital setting; <doi:10.1101/554725> , where methods are explained in detail.
Maintained by Niklas Willrich. Last updated 6 years ago.
0.5 match 3.18 score 1 dependents
plambertuliege
ordgam:Additive Model for Ordinal Data using Laplace P-Splines
Additive proportional odds model for ordinal data using Laplace P-splines. The combination of Laplace approximations and P-splines enable fast and flexible inference in a Bayesian framework. Specific approximations are proposed to account for the asymmetry in the marginal posterior distributions of non-penalized parameters. For more details, see Lambert and Gressani (2023) <doi:10.1177/1471082X231181173> ; Preprint: <arXiv:2210.01668>).
Maintained by Philippe Lambert. Last updated 2 years ago.
0.5 match 3.02 score 21 scripts
migurke
GenoPop:Genotype Imputation and Population Genomics Efficiently from Variant Call Formatted (VCF) Files
Tools for efficient processing of large, whole genome genotype data sets in variant call format (VCF). It includes several functions to calculate commonly used population genomic metrics and a method for reference panel free genotype imputation, which is described in the preprint Gurke & Mayer (2024) <doi:10.22541/au.172515591.10119928/v1>.
Maintained by Marie Gurke. Last updated 4 months ago.
0.5 match 3.00 score 6 scripts
chriscpritchard
PRISMA2020:Make Interactive 'PRISMA' Flow Diagrams
Systematic reviews should be described in a high degree of methodological detail. The 'PRISMA' Statement calls for a high level of reporting detail in systematic reviews and meta-analyses. An integral part of the methodological description of a review is a flow diagram. This package produces an interactive flow diagram that conforms to the 'PRISMA2020' preprint. When made interactive, the reader/user can click on each box and be directed to another website or file online (e.g. a detailed description of the screening methods, or a list of excluded full texts), with a mouse-over tool tip that describes the information linked to in more detail. Interactive versions can be saved as HTML files, whilst static versions for inclusion in manuscripts can be saved as HTML, PDF, PNG, SVG, PS or WEBP files.
Maintained by Chris Pritchard. Last updated 2 years ago.
0.5 match 1 stars 2.46 score 29 scripts
lmrodriguezr
enveomics.R:Various Utilities for Microbial Genomics and Metagenomics
A collection of functions for microbial ecology and other applications of genomics and metagenomics. Companion package for the Enveomics Collection (Rodriguez-R, L.M. and Konstantinidis, K.T., 2016 <DOI:10.7287/peerj.preprints.1900v1>).
Maintained by Luis M. Rodriguez-R. Last updated 1 months ago.
0.5 match 2.17 score 26 scripts
melinar
ZIprop:Permutations Tests and Performance Indicator for Zero-Inflated Proportions Response
Permutations tests to identify factor correlated to zero-inflated proportions response. Provide a performance indicator based on Spearman correlation to quantify the part of correlation explained by the selected set of factors. See details for the method at the following preprint e.g.: <https://hal.archives-ouvertes.fr/hal-02936779v3>.
Maintained by Melina Ribaud. Last updated 4 years ago.
0.5 match 2.08 score 12 scriptscran
kko:Kernel Knockoffs Selection for Nonparametric Additive Models
A variable selection procedure, dubbed KKO, for nonparametric additive model with finite-sample false discovery rate control guarantee. The method integrates three key components: knockoffs, subsampling for stability, and random feature mapping for nonparametric function approximation. For more information, see the accompanying paper: Dai, X., Lyu, X., & Li, L. (2021). “Kernel Knockoffs Selection for Nonparametric Additive Models”. arXiv preprint <arXiv:2105.11659>.
Maintained by Xiang Lyu. Last updated 3 years ago.
0.5 match 1 stars 2.00 score
jdgonzalezwork
tetrascatt:Acoustic Scattering for Complex Shapes by Using the DWBA
Uses the Distorted Wave Born Approximation (DWBA) to compute the acoustic backward scattering, the geometry of the object is formed by a volumetric mesh, composed of tetrahedrons. This computation is done efficiently through an analytical 3D integration that allows for a solution which is expressed in terms of elementary functions for each tetrahedron. It is important to note that this method is only valid for objects whose acoustic properties, such as density and sound speed, do not vary significantly compared to the surrounding medium. (See Lavia, Cascallares and Gonzalez, J. D. (2023). TetraScatt model: Born approximation for the estimation of acoustic dispersion of fluid-like objects of arbitrary geometries. arXiv preprint <arXiv:2312.16721>).
Maintained by Juan Domingo Gonzalez. Last updated 1 years ago.
0.5 match 2.00 score 5 scripts
chrislloyd58
exact.n:Exact Samples Sizes and Inference for Clinical Trials with Binary Endpoint
Allows the user to determine minimum sample sizes that achieve target size and power at a specified alternative. For more information, see “Exact samples sizes for clinical trials subject to size and power constraints” by Lloyd, C.J. (2022) Preprint <doi:10.13140/RG.2.2.11828.94085>.
Maintained by Chris J. Lloyd. Last updated 1 years ago.
0.5 match 1.70 scorecran
GeoAdjust:Accounting for Random Displacements of True GPS Coordinates of Data
The purpose is to account for the random displacements (jittering) of true survey household cluster center coordinates in geostatistical analyses of Demographic and Health Surveys program (DHS) data. Adjustment for jittering can be implemented either in the spatial random effect, or in the raster/distance based covariates, or in both. Detailed information about the methods behind the package functionality can be found in two preprints. Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad (2022) <arXiv:2202.11035v2>. Umut Altay, John Paige, Andrea Riebler, Geir-Arne Fuglstad (2022) <arXiv:2211.07442v1>.
Maintained by Umut Altay. Last updated 1 years ago.
0.5 match 1.70 score 1 scripts
junyuchen-econ
ablasso:Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models
Implements the Arellano-Bond estimation method combined with LASSO for dynamic linear panel models. See Chernozhukov et al. (2024) "Arellano-Bond LASSO Estimator for Dynamic Linear Panel Models". arXiv preprint <doi:10.48550/arXiv.2402.00584>.
Maintained by Junyu Chen. Last updated 1 months ago.
0.5 match 1 stars 1.30 score 1 scripts
e-caron
slm:Stationary Linear Models
Provides statistical procedures for linear regression in the general context where the errors are assumed to be correlated. Different ways to estimate the asymptotic covariance matrix of the least squares estimators are available. Starting from this estimation of the covariance matrix, the confidence intervals and the usual tests on the parameters are modified. The functions of this package are very similar to those of 'lm': it contains methods such as summary(), plot(), confint() and predict(). The 'slm' package is described in the paper by E. Caron, J. Dedecker and B. Michel (2019), "Linear regression with stationary errors: the R package slm", arXiv preprint <arXiv:1906.06583>.
Maintained by Emmanuel Caron. Last updated 5 years ago.
0.5 match 1.28 score 19 scripts
gloewing
sMTL:Sparse Multi-Task Learning
Implements L0-constrained Multi-Task Learning and domain generalization algorithms. The algorithms are coded in Julia allowing for fast implementations of the coordinate descent and local combinatorial search algorithms. For more details, see a preprint of the paper: Loewinger et al., (2022) <arXiv:2212.08697>.
Maintained by Gabriel Loewinger. Last updated 2 years ago.
0.5 match 1.00 score 8 scriptscran
cspec:Complete Discrete Fourier Transform (DFT) and Periodogram
Calculate the predictive discrete Fourier transform, complete discrete Fourier transform, complete periodogram, and tapered complete periodogram. This algorithm is based on the preprint "Spectral methods for small sample time series: A complete periodogram approach" (2020) by Sourav Das, Suhasini Subba Rao, and Junho Yang.
Maintained by Junho Yang. Last updated 5 years ago.
0.5 match 1.00 score 1 scriptscran
multiRDPG:Multiple Random Dot Product Graphs
Fits the Multiple Random Dot Product Graph Model and performs a test for whether two networks come from the same distribution. Both methods are proposed in Nielsen, A.M., Witten, D., (2018) "The Multiple Random Dot Product Graph Model", arXiv preprint <arXiv:1811.12172> (Submitted to Journal of Computational and Graphical Statistics).
Maintained by Agnes Martine Nielsen. Last updated 6 years ago.
0.5 match 1.00 scorecran
hdthreshold:Inference on Many Jumps in Nonparametric Panel Regression Models
Provides uniform testing procedures for existence and heterogeneity of threshold effects in high-dimensional nonparametric panel regression models. The package accompanies the paper Chen, Keilbar, Su and Wang (2023) "Inference on many jumps in nonparametric panel regression models". arXiv preprint <doi:10.48550/arXiv.2312.01162>.
Maintained by Georg Keilbar. Last updated 3 months ago.
0.5 match 1.00 score
rl1081
L2hdchange:L2 Inference for Change Points in High-Dimensional Time Series
Provides a method for detecting multiple change points in high-dimensional time series, targeting dense or spatially clustered signals. See Li et al. (2023) "L2 Inference for Change Points in High-Dimensional Time Series via a Two-Way MOSUM". arXiv preprint <arXiv:2208.13074>.
Maintained by Rui Lin. Last updated 2 years ago.
0.5 match 1 stars 1.00 score 1 scriptscran
l1spectral:An L1-Version of the Spectral Clustering
Provides an l1-version of the spectral clustering algorithm devoted to robustly clustering highly perturbed graphs using l1-penalty. This algorithm is described with more details in the preprint C. Champion, M. Champion, M. Blazère, R. Burcelin and J.M. Loubes, "l1-spectral clustering algorithm: a spectral clustering method using l1-regularization" (2022).
Maintained by Magali Champion. Last updated 3 years ago.
0.5 match 1.00 scorecran
latentgraph:Graphical Models with Latent Variables
Three methods are provided to estimate graphical models with latent variables: (1) Jin, Y., Ning, Y., and Tan, K. M. (2020) (preprint available); (2) Chandrasekaran, V., Parrilo, P. A. & Willsky, A. S. (2012) <doi:10.1214/11-AOS949>; (3) Tan, K. M., Ning, Y., Witten, D. M. & Liu, H. (2016) <doi:10.1093/biomet/asw050>.
Maintained by Yanxin Jin. Last updated 4 years ago.
0.5 match 1.00 scorecran
neuromplex:Neural Multiplexing Analysis
Statistical methods for whole-trial and time-domain analysis of single cell neural response to multiple stimuli presented simultaneously. The package is based on the paper by C Glynn, ST Tokdar, A Zaman, VC Caruso, JT Mohl, SM Willett, and JM Groh (2021) "Analyzing second order stochasticity of neural spiking under stimuli-bundle exposure", is in press for publication by the Annals of Applied Statistics. A preprint may be found at <arXiv:1911.04387>.
Maintained by Surya Tokdar. Last updated 4 years ago.
0.5 match 1.00 scorecran
cotrend:Consistent Co-Trending Rank Selection
Implements cointegration/co-trending rank selection algorithm in Guo and Shintani (2013) "Consistent co-trending rank selection when both stochastic and nonlinear deterministic trends are present". The Econometrics Journal 16: 473-483 <doi:10.1111/j.1368-423X.2012.00392.x>. Numbered examples correspond to Feb 2011 preprint <http://www.fas.nus.edu.sg/ecs/events/seminar/seminar-papers/05Apr11.pdf>.
Maintained by A. Christian Silva. Last updated 5 years ago.
0.5 match 1.00 score 2 scripts
