alpha |
The error tolerance level for the confidence and prediction bands. Note that this
@@ -181,11 +186,16 @@
It is possible to compare the calplot prediction bands with the
lod values if the lod() alpha and beta parameters are
half the value of the calplot() alpha parameter.
+ Author
+
+ Johannes Ranke
+ jranke@uni-bremen.de
Examples
-
+
diff --git a/docs/reference/din32645-1.png b/docs/reference/din32645-1.png
index cee27e9..27914e8 100644
Binary files a/docs/reference/din32645-1.png and b/docs/reference/din32645-1.png differ
diff --git a/docs/reference/din32645.html b/docs/reference/din32645.html
index 6af5152..b3ae61c 100644
--- a/docs/reference/din32645.html
+++ b/docs/reference/din32645.html
@@ -80,7 +80,7 @@
data(din32645)
+ data(din32645)
@@ -140,35 +140,42 @@
Analytica Chimica Acta 391, 105 - 126.
Examples
- #> [1] 0.2122306
diff --git a/docs/reference/index.html b/docs/reference/index.html
index d68dbd9..ea1ff81 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -79,7 +79,7 @@
inverse.predict(object, newdata, ...,
- ws, alpha=0.05, var.s = "auto")
+ inverse.predict(object, newdata, ...,
+ ws, alpha=0.05, var.s = "auto")
Arguments
@@ -199,8 +199,9 @@
Examples
#> $Prediction
+ m <- lm(y ~ x, data = massart97ex1)
+ inverse.predict(m, 15) # 6.1 +- 4.9
+ #> $Prediction
#> [1] 6.09381
#>
#> $`Standard Error`
@@ -211,7 +212,8 @@
#>
#> $`Confidence Limits`
#> [1] 1.187059 11.000561
-#> inverse.predict(m, 90) # 43.9 +- 4.9 #> $Prediction
+#> inverse.predict(m, 90) # 43.9 +- 4.9
+ #> $Prediction
#> [1] 43.93983
#>
#> $`Standard Error`
@@ -222,7 +224,8 @@
#>
#> $`Confidence Limits`
#> [1] 39.03178 48.84788
-#> #> $Prediction
+#> #> $Prediction
#> [1] 43.93983
#>
#> $`Standard Error`
@@ -236,18 +239,19 @@
#> #> $Prediction
+inverse.predict(m3.means, 15, ws = 1.67) # 5.9 +- 2.5
+ #> $Prediction
#> [1] 5.865367
#>
#> $`Standard Error`
@@ -258,7 +262,8 @@
#>
#> $`Confidence Limits`
#> [1] 3.387082 8.343652
-#> inverse.predict(m3.means, 90, ws = 0.145) # 44.1 +- 7.9 #> $Prediction
+#> inverse.predict(m3.means, 90, ws = 0.145) # 44.1 +- 7.9
+ #> $Prediction
#> [1] 44.06025
#>
#> $`Standard Error`
@@ -286,7 +291,7 @@
diff --git a/docs/reference/lod.html b/docs/reference/lod.html
index e5a1158..f647e8c 100644
--- a/docs/reference/lod.html
+++ b/docs/reference/lod.html
@@ -87,7 +87,7 @@
-
-
+
@@ -104,7 +104,7 @@
-
-
+
@@ -137,7 +137,7 @@
one-sided significance test).
- lod(object, ..., alpha = 0.05, beta = 0.05, method = "default", tol = "default")
+ lod(object, ..., alpha = 0.05, beta = 0.05, method = "default", tol = "default")
Arguments
@@ -207,8 +207,9 @@
Examples
- #> $x
+ #> $x
#> [1] 0.08655484
#>
#> $y
@@ -216,7 +217,8 @@
#>
# The critical value (decision limit, German Nachweisgrenze) can be obtained
# by using beta = 0.5:
-lod(m, alpha = 0.01, beta = 0.5) #> $x
+lod(m, alpha = 0.01, beta = 0.5)
+ #> $x
#> [1] 0.0698127
#>
#> $y
@@ -237,7 +239,7 @@
diff --git a/docs/reference/loq.html b/docs/reference/loq.html
index 2c7dc6a..6515e41 100644
--- a/docs/reference/loq.html
+++ b/docs/reference/loq.html
@@ -86,7 +86,7 @@
- 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
@@ -204,15 +204,17 @@
Examples
- #> $x
+ #> $x
#> [1] 13.97764
#>
#> $y
#> [1] 30.6235
#>
# We can get better by using replicate measurements
-loq(m, n = 3) #> $x
+loq(m, n = 3)
+ #> $x
#> [1] 9.971963
#>
#> $y
@@ -233,7 +235,7 @@
diff --git a/docs/reference/massart97ex1.html b/docs/reference/massart97ex1.html
index 95e6b3f..60f43ab 100644
--- a/docs/reference/massart97ex1.html
+++ b/docs/reference/massart97ex1.html
@@ -80,7 +80,7 @@
- data(massart97ex1)
+ data(massart97ex1)
@@ -150,7 +150,7 @@
diff --git a/docs/reference/massart97ex3.html b/docs/reference/massart97ex3.html
index a1efeba..13e28fd 100644
--- a/docs/reference/massart97ex3.html
+++ b/docs/reference/massart97ex3.html
@@ -80,7 +80,7 @@
massart97ex3
+ massart97ex3
@@ -139,19 +139,20 @@
Examples
#> $Prediction
#> [1] 5.865367
#>
#> $`Standard Error`
@@ -162,7 +163,8 @@
#>
#> $`Confidence Limits`
#> [1] 3.387082 8.343652
-#> #> $Prediction
+#> #> $Prediction
#> [1] 44.06025
#>
#> $`Standard Error`
@@ -176,15 +178,17 @@
#> #> $x
+ m0 <- lm(y ~ x, data = massart97ex3)
+ lod(m0)
+ #> $x
#> [1] 5.407085
#>
#> $y
#> [1] 13.63911
#> #> $x
#> [1] 9.627349
#>
#> $y
@@ -195,14 +199,15 @@
# If we are not using a variance function, we can use the weight from
# the above example as a first approximation (x = 15 is close to our
# loq approx 14 from above).
- loq( m3.means, w.loq = 1.67) #> $x
+ loq(m3.means, w.loq = 1.67)
+ #> $x
#> [1] 7.346195
#>
#> $y
#> [1] 17.90777
-#> # The weight for the loq should therefore be derived at x = 7.3 instead
-# of 15, but the graphical procedure of Massart (p. 201) to derive the
-# variances on which the weights are based is quite inaccurate anyway.
+#> # The weight for the loq should therefore be derived at x = 7.3 instead
+# of 15, but the graphical procedure of Massart (p. 201) to derive the
+# variances on which the weights are based is quite inaccurate anyway.
diff --git a/docs/reference/rl95_cadmium.html b/docs/reference/rl95_cadmium.html
index 509a0ab..c29ebae 100644
--- a/docs/reference/rl95_cadmium.html
+++ b/docs/reference/rl95_cadmium.html
@@ -80,7 +80,7 @@
|