getThetaRatio {CalciOMatic}R Documentation

Compute confidence intervals for parameters of calcium dynamics model fitted with the ratiometric approach

Description

The function getThetaRatio estimates confidence intervals for parameters a calcium dynamic model fitted to data estimated with the ratiometric transformation. The way these CIs are computed depends on the ciMode parameter.

Usage

getThetaRatio(calcium_ratio_fit,
              ciMode = c("normalApprox", "likelihoodRatio"), ...)

Arguments

calcium_ratio_fit an object of class "ratio_fit"
ciMode should the normal approximation ("normal") or the likelihood ratio ("ratio") be used to obtain the CI?
... not used

Details

The ciMode argument specifies which approach to use to estimate the CIs. If set to "normal", the quadratic approximation of the log-likelihood applies, and the 95% CIs are given as t(0.975,dof)*se(p), where t is the Student quantile function, dof is the number of degrees of freedom, se(p) is the standard error associated to the estimation of parameter p (given by the inverse of the square root of the diagonal of the hessian matrix returned by "optim"). If ciMode is set to "likelihoodRatio", we make use of the likelihood ratio statistics (Davison, 2003).

Value

A matrix with 2 rows and N columns, corresponding to the number of parameters of the calcium dynamics model. Each column gives the lower and upper bound of the 95% confidence interval for each parameter.

Author(s)

Sebastien Joucla sebastien.joucla@parisdescartes.fr

References

Davison AC (2003), Statistical Models, Cambridge University Press

Examples

## Load the data from cockroach olfactory interneurons
data(inVitro)

## Calibrated parameters
R_min <- list(value=0.136, mean=0.136, se=0.00363, USE_se=TRUE)
R_max <- list(value=2.701, mean=2.701, se=0.151,   USE_se=TRUE)
K_eff <- list(value=3.637, mean=3.637, se=0.729,   USE_se=TRUE)
K_d   <- list(value=0.583, mean=0.583, se=0.123,   USE_se=TRUE)

## Create the data frame containing the physiological data
## (experiment #2, stimulation #2)
## G and s_ro are the respectively the gain of the CCD camera
## and the standard deviation of its read-out process
physioData <- ratioExpPhysio(dataset="inVitro",
                             expe=2, stim=2,
                             idxOn=10,
                             R_min=R_min, R_max=R_max,
                             K_eff=K_eff, K_d=K_d,
                             G=0.146, s_ro=16.4,
                             alphamethod=FALSE)

## Retrieve the calcium concentration from the data frame
Ca_noisy <- caFromDf(df           = physioData,
                     numTransient = 2,
                     Plot         = FALSE)

## Perform a ratiometric fit
physioRatioFit <- ratioFitFromCa(Ca  = Ca_noisy,
                                 t   = attr(Ca_noisy,"Time"),
                                 tOn = attr(Ca_noisy, "tOn"),
                                 type = "mono",
                                 AfterPeak = 14)

## Compute the confidence interval
## using the likelihood ratio statistics
CI <- getThetaRatio(physioRatioFit,
                    ciMode = "likelihoodRatio")

print(CI)

[Package CalciOMatic version 1.1-3 Index]