pc: pc

GITHUB

GerritEichner/kader: Kernel Adaptive Density Estimation and Regression

R: pc
pcR Documentation
pc

pc: pc

CRAN

kader: Kernel Adaptive Density Estimation and Regression

R: pc
pcR Documentation
pc

PCS: PCS

GITHUB

lvalnegri/dmpkg.bnduk: Boundaries related to UK geographies

R: PCS
PCSR Documentation
PCS

ggtrans: 谷歌翻译

GITHUB

Gabegit/gmtools: My small tools for efficiency

R: 谷歌翻译
ggtransR Documentation
谷歌翻译

PC: simulated PCs

CRAN

SC.MEB: Spatial Clustering with Hidden Markov Random Field using Empirical Bayes

R: simulated PCs
PCR Documentation
simulated PCs

PCS: PCS Dataset

CRAN

lbreg: Log-Binomial Regression with Constrained Optimization

R: PCS Dataset
PCSR Documentation
PCS Dataset

pcs: Table pcs

GITHUB

stephLH/apogee: Fonctions autour du referentiel Apogee

R: Table pcs
pcsR Documentation
Table pcs

pcs: Table pcs

GITHUB

ove-ut3/apogee: Fonctions autour du referentiel Apogee

R: Table pcs
pcsR Documentation
Table pcs

pc: Peter & Clark Algorithm (PC)

GITHUB

rlebron-bioinfo/gnlearn: Genetic Network Learning

R: Peter & Clark Algorithm (PC)
pcR Documentation
Peter & Clark Algorithm (PC)

PCS: Calculate the Probability of Correct Selection (PCS)

CRAN

PCS: Calculate the Probability of Correct Selection (PCS)

Package: PCS
Type: Package
Title: Calculate the Probability of Correct Selection (PCS)

man/PCS-package.Rd

PC: Principal component (PC) estimation of the approximate factor...

CRAN

GCCfactor: GCC Estimation of the Multilevel Factor Model

R: Principal component (PC) estimation of the approximate factor...
const macros = { "\\R": "\\textsf{R}", "\\code

pc: Estimate the Equivalence Class of a DAG using the PC...

RFORGE

pcalg: Methods for Graphical Models and Causal Inference

R: Estimate the Equivalence Class of a DAG using the PC...
const macros = { "\\R": "\\textsf{R}", "\\code

pc: Estimate the Equivalence Class of a DAG using the PC...

CRAN

pcalg: Methods for Graphical Models and Causal Inference

R: Estimate the Equivalence Class of a DAG using the PC...
const macros = { "\\R": "\\textsf{R}", "\\code

pcs: Prepare Control Units pcs and pts create data frames with the...

CRAN

PanelMatch: Matching Methods for Causal Inference with Time-Series Cross-Sectional Data

R: Prepare Control Units pcs and pts create data frames with the...
const macros = { "\\R": "\\textsf{R}", "\\code

f_weibo_app_followtags: 文本向量词云

GITHUB

yibochen/weiBor: fetch and analyse weibo data

R: 文本向量词云
f_weibo_app_followtagsR Documentation
文本向量词云

telegram: telegram.

CRAN

telegram: R Wrapper Around the Telegram Bot API

R: telegram.
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

telegram: telegram.

GITHUB

lbraglia/telegram: R Wrapper Around the Telegram Bot API

R: telegram.
const macros = { "\\R": "\\textsf{R}", "\\code": "\\texttt"};
function processMathHTML() {

pc-multvar: Multivariate PC priors

GITHUB

inbo/INLA: Full Bayesian Analysis of Latent Gaussian Models using Integrated Nested Laplace Approximations

R: Multivariate PC priors
pc.multvarR Documentation
Multivariate PC priors

pc-multvar: Multivariate PC priors

GITHUB

INBO-BMK/INLA: Full Bayesian Analysis of Latent Gaussian Models using Integrated Nested Laplace Approximations

R: Multivariate PC priors
pc.multvarR Documentation
Multivariate PC priors

pc-multvar: Multivariate PC priors

GITHUB

andrewzm/INLA: Functions which allow to perform full Bayesian analysis of latent Gaussian models using Integrated Nested Laplace Approximaxion

R: Multivariate PC priors
pc.multvarR Documentation
Multivariate PC priors