From f4fcef8228ebd5a1a73bc6edc47b5efa259c2e20 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 23 Mar 2022 10:32:36 +0100 Subject: Use 'investr' conditionally in tests, updates Most prominently, a README was added, giving a nice overview for the people visiting the github page, the package page on CRAN, or the online docs at pkgdown.jrwb.de. The maintainer e-mail address was also updated. --- docs/reference/calplot.lm.html | 218 +++++++++++++---------------------------- 1 file changed, 68 insertions(+), 150 deletions(-) (limited to 'docs/reference/calplot.lm.html') diff --git a/docs/reference/calplot.lm.html b/docs/reference/calplot.lm.html index b041a8d..7865a66 100644 --- a/docs/reference/calplot.lm.html +++ b/docs/reference/calplot.lm.html @@ -1,68 +1,13 @@ - - - - - - - -Plot calibration graphs from univariate linear models — calplot • chemCal - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Plot calibration graphs from univariate linear models — calplot • chemCal - - - - + + -
-
- -
- -
+

Plot calibration graphs from univariate linear models

@@ -125,102 +57,88 @@ as confidence, and, for unweighted regression, prediction bands.

- 
calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"),
-    xlab = "Concentration", ylab = "Response", legend_x = "auto",
-    alpha=0.05, varfunc = NULL)
- -

Arguments

- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
object

A univariate model object of class lm or - rlm - with model formula y ~ x or y ~ x - 1.

xlim

The limits of the plot on the x axis.

ylim

The limits of the plot on the y axis.

xlab

The label of the x axis.

ylab

The label of the y axis.

legend_x

An optional numeric value for adjusting the x coordinate of the legend.

alpha

The error tolerance level for the confidence and prediction bands. Note that this - includes both tails of the Gaussian distribution, unlike the alpha and beta parameters - used in lod (see note below).

varfunc

The variance function for generating the weights in the model. - Currently, this argument is ignored (see note below).

- -

Value

+
+ 
calplot(object, xlim = c("auto", "auto"), ylim = c("auto", "auto"),
+    xlab = "Concentration", ylab = "Response", legend_x = "auto",
+    alpha=0.05, varfunc = NULL)
+
+
+

Arguments

+
object
+

A univariate model object of class lm or + rlm + with model formula y ~ x or y ~ x - 1.

+
xlim
+

The limits of the plot on the x axis.

+
ylim
+

The limits of the plot on the y axis.

+
xlab
+

The label of the x axis.

+
ylab
+

The label of the y axis.

+
legend_x
+

An optional numeric value for adjusting the x coordinate of the legend.

+
alpha
+

The error tolerance level for the confidence and prediction bands. Note that this + includes both tails of the Gaussian distribution, unlike the alpha and beta parameters + used in lod (see note below).

+
varfunc
+

The variance function for generating the weights in the model. + Currently, this argument is ignored (see note below).

+
+
+

Value

A plot of the calibration data, of your fitted model as well as lines showing the confidence limits. Prediction limits are only shown for models from unweighted regression.

-

Note

- +
+
+

Note

Prediction bands for models from weighted linear regression require weights for the data, for which responses should be predicted. Prediction intervals using weights e.g. from a variance function are currently not supported by - the internally used function predict.lm, therefore, + the internally used function predict.lm, therefore, calplot does not draw prediction bands for such models.

It is possible to compare the calplot prediction bands with the - lod values if the lod() alpha and beta parameters are + lod values if the lod() alpha and beta parameters are half the value of the calplot() alpha parameter.

-

Author

- +
+
+

Author

Johannes Ranke - jranke@uni-bremen.de

+ jranke@uni-bremen.de

+
-

Examples

- 
data(massart97ex3)
-m <- lm(y ~ x, data = massart97ex3)
-calplot(m)
-
+
+

Examples

+ 
data(massart97ex3)
+m <- lm(y ~ x, data = massart97ex3)
+calplot(m)
+
+
+
+
-
- - + + -- cgit v1.2.1