Predict x from y for a linear calibration — inverse.predict

From 966da79af48c371c05dd8011702ef2bd3b1d1e03 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 1 Mar 2018 10:35:09 +0100 Subject: Static documentation rebuilt using current pkgdown --- docs/reference/inverse.predict.html | 85 +++++++++++++++++++++++-------------- 1 file changed, 52 insertions(+), 33 deletions(-) (limited to 'docs/reference/inverse.predict.html') diff --git a/docs/reference/inverse.predict.html b/docs/reference/inverse.predict.html index af05986..32f8f44 100644 --- a/docs/reference/inverse.predict.html +++ b/docs/reference/inverse.predict.html @@ -18,19 +18,37 @@ + + + + + + + - + + + @@ -85,43 +103,44 @@ This is elaborated in the package vignette.

inverse.predict(object, newdata, …,
+    inverse.predict(object, newdata, …,
   ws, alpha=0.05, var.s = "auto")
     
      Arguments
-    
-      object
-      
-    A univariate model object of class lm or 
+    
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    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
+    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.
-  
-    
+    overrides ws.
     
     Value
 
@@ -201,7 +220,7 @@
 
 
 
-  Site built with pkgdown.
+  Site built with pkgdown.
 
 
       
-- 
cgit v1.2.1

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 + 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`. - - + overrides `ws`.