Search results for 'WA 0859 3970 0884 \[\[Hatiga Konstruksi\]\] RAB Keramik Granit Dinding 60 x 60 Murah Baki Sukoharjo'

snoweye/pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

, and these are functions
to print and summary objects.
Usage

60-print: Functions for Printing or Summarizing Objects According

pmclust: Parallel Model-Based Clustering using Expectation-Gathering-Maximization Algorithm for Finite Mixture Gaussian Model

to print and summary objects.
Usage
## S3 method for class 'pmclust'

WA: Weighted averaging (WA) regression and calibration

rioja: Analysis of Quaternary Science Data

assemblages using weighted averaging (WA) regression and calibration.
Usage
WA(y, x, mono=FALSE, tolDW = FALSE, use.N2=TRUE

WA: Weighted averaging (WA) regression and calibration

nsj3/rioja: Analysis of Quaternary Science Data

assemblages using weighted averaging (WA) regression and calibration.
Usage
WA(y, x, mono=FALSE, tolDW = FALSE, use.N2=TRUE

R/60-interval_index-internals.R:

# Runtime: O(1).
# Central type/shape gate for public interval methods.
# **Inputs:** object `x`.

RAB: Compute the relative absolute bias of multiple estimators

SimDesign: Structure for Organizing Monte Carlo Simulation Designs

estimators.
Usage
RAB(x, percent = FALSE, unname = FALSE)

TCGA.BC.gene.exp.2k.60: TCGA BRCA expression data

BIOC

OmicCircos: High-quality circular visualization of omics data

of TCGA Breast Cancer expression data from 500 genes and 60 samples
Author(s)
Ying Hu <yhu@mail.nih.gov>

WA: While-Alive Loss Rate for Recurrent Event in the Presence of Death

WA: While-Alive Loss Rate for Recurrent Event in the Presence of Death

Package: WA
Type: Package
Title: While-Alive Loss Rate for Recurrent Event in the Presence of

RAB: real adaboost (Friedman et al

BIOC

MLInterfaces: Uniform interfaces to R machine learning procedures for data in Bioconductor containers

... a demonstration version
Usage
RAB(formula, data, maxiter=200, maxdepth=1)

RAB: real adaboost (Friedman et al

lgatto/MLInterfaces: Uniform interfaces to R machine learning procedures for data in Bioconductor containers

... a demonstration version
Usage
RAB(formula, data, maxiter=200, maxdepth=1)

TCGA.BC.cnv.2k.60: copy number data of TCGA Breast Cancer

BIOC

OmicCircos: High-quality circular visualization of omics data

Description
Examples of TCGA Breast Cancer DNA copy number data from 500 genes and 60 samples.
Author(s)

R/60-interval_index-monoids.R:

# Runtime: O(1).
# Determines endpoint scalar domain tag.
# **Inputs

R/60-interval_index-indexing.R:

-.interval_index
#' @param x An `interval_index`.
#' @param i Index input.

R/60-interval_index-methods.R:

# Public cast to plain flexseq while dropping interval-specific behavior.
# **Inputs:** `x` interval_index.
# **Outputs

R/60-interval_index-mutations.R:

# Internal insert engine preserving interval ordering by start.
# **Inputs:** `x` interval_index; `entry

R/60-interval_index-apply.R:

# **Inputs:**
# - `x`: interval_index.
# - `f`: function(value, start, end, name, ...) -> new value.

WA: SpatialPolygonsDataFrame for the state of Washington, USA

tmcd82070/SDraw: Spatially Balanced Samples of Spatial Objects

of Washington.
Usage
data("WA")

R/60-interval_index-print.R: