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/loq.html | 249 ++++++++++++++++-------------------------------- 1 file changed, 84 insertions(+), 165 deletions(-) (limited to 'docs/reference/loq.html') diff --git a/docs/reference/loq.html b/docs/reference/loq.html index 973b1ff..0960251 100644 --- a/docs/reference/loq.html +++ b/docs/reference/loq.html @@ -1,73 +1,18 @@ - - - - - - - -Estimate a limit of quantification (LOQ) — loq • chemCal - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -Estimate a limit of quantification (LOQ) — loq • chemCal - - - - - - - - - - - - - + + -
-
- -
- -
+

Estimate a limit of quantification (LOQ)

@@ -132,119 +64,106 @@ $$L = k c(L)$$ where c(L) is half of the length of the confidence interval at the limit L (DIN 32645, equivalent to ISO 11843). c(L) is internally estimated by - inverse.predict, and L is obtained by iteration.

+ inverse.predict, and L is obtained by iteration.

- 
loq(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto",
-    var.loq = "auto", tol = "default")
+
+ 
loq(object, ..., alpha = 0.05, k = 3, n = 1, w.loq = "auto",
+    var.loq = "auto", tol = "default")
+
-

Arguments

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

A univariate model object of class lm or - rlm +

+

Arguments

+
object
+

A univariate model object of class lm or + rlm with model formula y ~ x or y ~ x - 1, optionally from a weighted regression. If weights are specified in the model, either w.loq or var.loq have to - be specified.

alpha

The error tolerance for the prediction of x values in the calculation.

...

Placeholder for further arguments that might be needed by - future implementations.

k

The inverse of the maximum relative error tolerated at the - desired LOQ.

n

The number of replicate measurements for which the LOQ should be - specified.

w.loq

The weight that should be attributed to the LOQ. Defaults + be specified.

+
alpha
+

The error tolerance for the prediction of x values in the calculation.

+
...
+

Placeholder for further arguments that might be needed by + future implementations.

+
k
+

The inverse of the maximum relative error tolerated at the + desired LOQ.

+
n
+

The number of replicate measurements for which the LOQ should be + specified.

+
w.loq
+

The weight that should be attributed to the LOQ. Defaults to one for unweighted regression, and to the mean of the weights - for weighted regression. See massart97ex3 for + for weighted regression. See massart97ex3 for an example how to take advantage of knowledge about the - variance function.

var.loq

The approximate variance at the LOQ. The default value is - calculated from the model.

tol

The default tolerance for the LOQ on the x scale is the value of the + variance function.

+
var.loq
+

The approximate variance at the LOQ. The default value is + calculated from the model.

+
tol
+

The default tolerance for the LOQ on the x scale is the value of the smallest non-zero standard divided by 1000. Can be set to a - numeric value to override this.

- -

Value

- + numeric value to override this.

+
+
+

Value

The estimated limit of quantification for a model used for calibration.

-

Note

- +
+
+

Note

- IUPAC recommends to base the LOQ on the standard deviation of the signal where x = 0. - The calculation of a LOQ based on weighted regression is non-standard and therefore not tested. Feedback is welcome.

-

See also

- -

Examples for din32645

- -

Examples

- 
m <- lm(y ~ x, data = massart97ex1)
-loq(m)
-
#> $x
-#> [1] 13.97764
-#> 
-#> $y
-#> [1] 30.6235
-#> 

-# We can get better by using replicate measurements
-loq(m, n = 3)
-
#> $x
-#> [1] 9.971963
-#> 
-#> $y
-#> [1] 22.68539
-#>
+
+
+

See also

+

Examples for din32645

+
+ +
+

Examples

+ 
m <- lm(y ~ x, data = massart97ex1)
+loq(m)
+#> $x
+#> [1] 13.97764
+#> 
+#> $y
+#> [1] 30.6235
+#> 
+
+# We can get better by using replicate measurements
+loq(m, n = 3)
+#> $x
+#> [1] 9.971963
+#> 
+#> $y
+#> [1] 22.68539
+#> 
+
+
+
- - - + + -- cgit v1.2.1