Returns the results of the analyses performed by det_order() function.
Value
It prints a summary of the analysis in the phase space, the reaction order, and the regression results.
Details
The function prints:
the linear regression performed in the phase space, together with the estimated n value and its 95% confidence interval
a brief conclusion on the results obtained in the phase space stating which reaction order should be preferred
the (non-)linear regression performed with parameters associated statistics. If a non-linear regression has been performed, the most common goodness-of-fit measures calculated with
goodness_of_fit()are printed
Examples
t <- c(0, 4, 8, 12, 16, 20)
conc <- c(1, 0.51, 0.24, 0.12, 0.07, 0.02)
err <- c(0.02, 0.05, 0.04, 0.04, 0.03, 0.02)
dframe <- data.frame(t, conc, err)
res <- det_order(dframe)
#> Reaction order estimated: 1
results(res)
#>
#> Linear regression in the phase space:
#> log(dx/dt)= 0.9 log(x) + ( -1.85 )
#>
#> Estimate of n:
#>
#> Estimate Std. Error t value Pr(>|t|)
#> 8.950329e-01 6.381322e-02 1.402582e+01 7.848645e-04
#>
#> Confidence interval of n:
#> 2.5 % 97.5 %
#> 0.6919508 1.0981151
#>
#> Statistical analysis indicates that an order 1 degradation kineitc model is likely to describe the data.
#> The null hypothesis H0:
#> "The process is described by an order 1kinetic model"
#> cannot be rejected.
#>
#> Non-linear least squares regression was performed with an order 1 kinetic model:
#>
#> Estimate of k:
#> Estimate Std. Error t value Pr(>|t|)
#> k 0.1756979 0.003543597 49.5818 6.306689e-08
#> Waiting for profiling to be done...
#> Confidence interval of k:
#> 2.5% 97.5%
#> 0.1670824 0.1851654
#>
#> Goodness-of-fit:
#> Value
#> AIC: -36.0007045
#> AICc: -35.0007045
#> BIC: -36.4171856
#> RMSE: 0.3010471
#> Chi-sq_red: 0.1344415
#> -----------------------------------------------------
#>