The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Type: Package
Title: Perform Weighted Linear Regression for Calibration Curve
Version: 0.1.6
Author: Yonghui Dong
Maintainer: Yonghui Dong <yonghui.dong@gmail.com>
Description: Automated assessment and selection of weighting factors for accurate quantification using linear calibration curve. In addition, a 'shiny' App is provided, allowing users to analyze their data using an interactive graphical user interface, without any programming requirements.
Depends: R (≥ 3.5.0)
Imports: plotly, dplyr, stats, magrittr, shiny, bs4Dash, fresh, DT, tools, readxl, rmarkdown, readr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.2
NeedsCompilation: no
Packaged: 2021-11-09 21:26:31 UTC; dong
Repository: CRAN
Date/Publication: 2021-11-09 21:40:02 UTC

Perform Calibration

Description

Perform calibration

Usage

doCalibration(DF, weights = NULL)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'

weights

default is NULL

Value

dataframe, the quantification result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, "unknown"), each = 3)
Response <- c(133, 156, 177, 6650, 7800, 8850, 13300, 15600, 17700, 156, 1450, 1400)
DF <- cbind.data.frame(Concentration = Concentration, Response = Response)
result <- doCalibration(DF)

Evaluate Different Weighting Factors

Description

Evaluate different weighting factors.

Usage

doEvaluation(DF, p = 0.05, userWeights = NULL)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'

p

p-value, default is 0.05

userWeights

user defined weights in linear regression, default is NULL. User can easily define weights, e.g., "1/x", "1/x^2", "1/y"

Value

dataframe, weighting factor evaluation result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, 500), each = 3)
Response <- c(133, 156, 177, 1300, 1450, 1600, 4000, 3881, 3700, 140000, 139000, 140000)
DF <- cbind.data.frame(Concentration = Concentration, Response = Response)
result <- doEvaluation(DF)

Perform F Test

Description

perform F test to evaluate homoscedasticity.

Usage

doFtest(DF, p = 0.01, lower.tail = FALSE)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'

p

p-value

lower.tail

default is FALSE

Value

dataframe, F test result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, 500), each = 3)
Response <- c(133, 156, 177, 1300, 1450, 1600, 4000, 3881, 3700, 140000, 139000, 140000)
DF <- cbind.data.frame(Concentration, Response)
result <- doFtest(DF, p = 0.01)

Perform Weighted Linear Regression

Description

Perform weighted linear regression and evaluate by using summed residual.

Usage

doWlm(DF, weights = NULL)

Arguments

DF

data frame, it must contain a column named 'Concentration' and a column named 'Response'

weights

the weights used in linear regression, default is NULL. User can easily define weights, e.g., "1/x", "1/x^2", "1/y"

Value

list, weighted linear regression result

Author(s)

Yonghui Dong

Examples

Concentration <- rep(c(10, 50, 100, 500), each = 3)
Response <- c(133, 156, 177, 1300, 1450, 1600, 4000, 3881, 3700, 140000, 139000, 140000)
DF <- cbind.data.frame(Concentration = Concentration, Response = Response)
result <- doWlm(DF, weights = "1/x^2")

expData

Description

Two example data set: one with internal standards (IS), and one without IS

Usage

expData

Format

A list with 2 data frames:

noSTD

the example data without IS

STD

the example data with IS


Run CCWeights Gui

Description

Run CCWeights Gui.

Usage

runGui()

Value

Gui

Author(s)

Yonghui Dong

Examples

if(interactive()){}

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.