R: Examples for 'MASS::muscle'

### ** Examples

## IGNORE_RDIFF_BEGIN
A <- model.matrix(~ Strip - 1, data=muscle)
rats.nls1 <- nls(log(Length) ~ cbind(A, rho^Conc),
   data = muscle, start = c(rho=0.1), algorithm="plinear")
(B <- coef(rats.nls1))

          rho .lin.StripS01 .lin.StripS02 .lin.StripS03 .lin.StripS04 
   0.07776401    3.08304824    3.30137838    3.44562531    2.80464434 
.lin.StripS05 .lin.StripS06 .lin.StripS07 .lin.StripS08 .lin.StripS09 
   2.60835015    3.03357725    3.52301734    3.38711844    3.46709396 
.lin.StripS10 .lin.StripS11 .lin.StripS12 .lin.StripS13 .lin.StripS14 
   3.81438456    3.73878664    3.51332581    3.39741115    3.47088608 
.lin.StripS15 .lin.StripS16 .lin.StripS17 .lin.StripS18 .lin.StripS19 
   3.72895847    3.31863862    3.37938673    2.96452195    3.58468686 
.lin.StripS20 .lin.StripS21        .lin22 
   3.39628029    3.36998872   -2.96015460

st <- list(alpha = B[2:22], beta = B[23], rho = B[1])
(rats.nls2 <- nls(log(Length) ~ alpha[Strip] + beta*rho^Conc,
                  data = muscle, start = st))

Nonlinear regression model
  model: log(Length) ~ alpha[Strip] + beta * rho^Conc
   data: muscle
alpha..lin.StripS01 alpha..lin.StripS02 alpha..lin.StripS03 alpha..lin.StripS04 
            3.08305             3.30138             3.44563             2.80464 
alpha..lin.StripS05 alpha..lin.StripS06 alpha..lin.StripS07 alpha..lin.StripS08 
            2.60835             3.03358             3.52302             3.38712 
alpha..lin.StripS09 alpha..lin.StripS10 alpha..lin.StripS11 alpha..lin.StripS12 
            3.46709             3.81438             3.73879             3.51333 
alpha..lin.StripS13 alpha..lin.StripS14 alpha..lin.StripS15 alpha..lin.StripS16 
            3.39741             3.47089             3.72896             3.31864 
alpha..lin.StripS17 alpha..lin.StripS18 alpha..lin.StripS19 alpha..lin.StripS20 
            3.37939             2.96452             3.58469             3.39628 
alpha..lin.StripS21         beta..lin22             rho.rho 
            3.36999            -2.96015             0.07776 
 residual sum-of-squares: 1.045

Number of iterations to convergence: 0 
Achieved convergence tolerance: 4.923e-06

## IGNORE_RDIFF_END

Muscle <- with(muscle, {
Muscle <- expand.grid(Conc = sort(unique(Conc)), Strip = levels(Strip))
Muscle$Yhat <- predict(rats.nls2, Muscle)
Muscle <- cbind(Muscle, logLength = rep(as.numeric(NA), 126))
ind <- match(paste(Strip, Conc),
            paste(Muscle$Strip, Muscle$Conc))
Muscle$logLength[ind] <- log(Length)
Muscle})

lattice::xyplot(Yhat ~ Conc | Strip, Muscle, as.table = TRUE,
   ylim = range(c(Muscle$Yhat, Muscle$logLength), na.rm = TRUE),
   subscripts = TRUE, xlab = "Calcium Chloride concentration (mM)",
   ylab = "log(Length in mm)", panel =
   function(x, y, subscripts, ...) {
      panel.xyplot(x, Muscle$logLength[subscripts], ...)
      llines(spline(x, y))
   })

Examples for 'MASS::muscle'

Effect of Calcium Chloride on Muscle Contraction in Rat Hearts