From 73e650114af77582238abf5273e63005e0b2287e Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Mon, 6 Mar 2017 17:00:48 +0100 Subject: Static documentation now built by pkgdown::build_site() --- docs/reference/inverse.predict.html | 211 ++++++++++++++++++++++++++++++++++++ 1 file changed, 211 insertions(+) create mode 100644 docs/reference/inverse.predict.html (limited to 'docs/reference/inverse.predict.html') diff --git a/docs/reference/inverse.predict.html b/docs/reference/inverse.predict.html new file mode 100644 index 0000000..60d169c --- /dev/null +++ b/docs/reference/inverse.predict.html @@ -0,0 +1,211 @@ + + + + + + + + +Predict x from y for a linear calibration — inverse.predict • chemCal + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+
+
+

Predict x from y for a linear calibration

+
+ + +

This function predicts x values using a univariate linear model that has been + generated for the purpose of calibrating a measurement method. Prediction + intervals are given at the specified confidence level. + The calculation method was taken from Massart et al. (1997). In particular, + Equations 8.26 and 8.28 were combined in order to yield a general treatment + of inverse prediction for univariate linear models, taking into account + weights that have been used to create the linear model, and at the same + time providing the possibility to specify a precision in sample measurements + differing from the precision in standard samples used for the calibration. + This is elaborated in the package vignette.

+ + + 
inverse.predict(object, newdata, …,
+  ws, alpha=0.05, var.s = "auto")
+ +

Arguments

+
+
object
+
+ A univariate model object of class lm or + rlm + with model formula y ~ x or y ~ x - 1. +
+
newdata
+
+ A vector of observed y values for one sample. +
+
…
+
+ Placeholder for further arguments that might be needed by + future implementations. +
+
ws
+
+ The weight attributed to the sample. This argument is obligatory + if object has weights. +
+
alpha
+
+ The error tolerance level for the confidence interval to be reported. +
+
var.s
+
+ The estimated variance of the sample measurements. The default is to take + the residual standard error from the calibration and to adjust it + using ws, if applicable. This means that var.s + overrides ws. +
+
+ +

Value

+ +

A list containing the predicted x value, its standard error and a + confidence interval.

+ +

Note

+ +

The function was validated with examples 7 and 8 from Massart et al. (1997).

+ +

References

+ +

Massart, L.M, Vandenginste, B.G.M., Buydens, L.M.C., De Jong, S., Lewi, P.J., + Smeyers-Verbeke, J. (1997) Handbook of Chemometrics and Qualimetrics: Part A, + p. 200

+ + +

Examples

+ 
# This is example 7 from Chapter 8 in Massart et al. (1997)
+data(massart97ex1)
+m <- lm(y ~ x, data = massart97ex1)
+inverse.predict(m, 15)        #  6.1 +- 4.9
#> $Prediction
+#> [1] 6.09381
+#> 
+#> $`Standard Error`
+#> [1] 1.767278
+#> 
+#> $Confidence
+#> [1] 4.906751
+#> 
+#> $`Confidence Limits`
+#> [1]  1.187059 11.000561
+#> 
inverse.predict(m, 90)        # 43.9 +- 4.9
#> $Prediction
+#> [1] 43.93983
+#> 
+#> $`Standard Error`
+#> [1] 1.767747
+#> 
+#> $Confidence
+#> [1] 4.908053
+#> 
+#> $`Confidence Limits`
+#> [1] 39.03178 48.84788
+#> 
inverse.predict(m, rep(90,5)) # 43.9 +- 3.2
#> $Prediction
+#> [1] 43.93983
+#> 
+#> $`Standard Error`
+#> [1] 1.141204
+#> 
+#> $Confidence
+#> [1] 3.168489
+#> 
+#> $`Confidence Limits`
+#> [1] 40.77134 47.10832
+#>
+
+ +
+ + +
+ + + -- cgit v1.2.1