Description Slots Methods Author(s) See Also Examples
calib.fit utilizes two main model types, linear and logistic regression for the purpose of standard curve fitting. It also incorporates several alternatives within each model type to allow for more flexible and reliable fitting.
coefficients
:Estimates of the coefficients
se.coefficients
:Estimates of the standard errors for the coefficients
sigma
:Standard deviation of model
cov.unscaled
:Unscaled variance-covariance matrix of the coefficients
pom
:Whether or not POM model was used, TRUE or FALSE.
theta
:The estimated value of POM parameter theta
df.residual
:The residual degree of freedom
fitted.values
:The estimated fitted values
residuals
:The values of the residuals
method
:Which algorithm was used to do the optimization (i.e. ML, RML, EM, etc.)
kused
:The number of iteration to convergence of the GLS fit
status
:Indicated whether the algorithm converged
x
:The x values
y
:The y values
logParm
:Indicated whether a log parameterization of the model used
m
:The number of repeated measures used in the model
cv
:Coefficient of variation used
mdc
:Minimum detectable concentration
rdl
:Reliable detection limit
loq
:Limit of quantitation
gradient
:The gradient matrix based off of the final parameter estimates
lof.test
:An slot returing information from a lack of fit (LOF) test.
var.model
:The type of variance model used
conf.level
:Confidence level used
type
:Whether, fpl, tpl, thpl, lin or quad was used.
rdlwarn
:The general model type used, fpl, thpl or lin
Accessor function for coefficients
Accessor function for coefficients
Accessor function for the fitted values
Accessor function for the limit of quanitization
Accessor function for the minimum detectable concentration
Plot methods for object of class calib.fit
Print results from calibration curve fit.
Accessor function the reliable detection limit
Accessor function for residuals
Accessor function for residuals
Same as print
Same as print
Perry Haaland, Elaine McVey, Daniel Samarov
1 | showClass("calib.fit")
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