Hello, 

I'm new here, but will try to be as specific and complete as possible. I'm
trying to use “lm“ to first estimate parameter values from a set of
calibration measurements, and then later to use those estimates to calculate
another set of values with “predict.lm”.

First I have a calibration dataset of absorbance values measured from
standard solutions with known concentration of Bromide:

> stds
      abs conc
1 -0.0021    0
2  0.1003  200
3  0.2395  500
4  0.3293  800

On this small calibration series, I perform a linear regression to find the
parameter estimates of the relationship between absorbance (abs) and
concentration (conc):

> linear1 <- lm(abs~conc, data=stds)
> summary(linear1)

Call:
lm(formula = abs ~ conc, data = stds)

Residuals:
        1         2         3         4 
-0.012600  0.006467  0.020667 -0.014533 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)   
(Intercept) 1.050e-02  1.629e-02   0.645  0.58527   
conc        4.167e-04  3.378e-05  12.333  0.00651 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 0.02048 on 2 degrees of freedom
Multiple R-squared: 0.987,      Adjusted R-squared: 0.9805 
F-statistic: 152.1 on 1 and 2 DF,  p-value: 0.00651 





Now I come with another dataset, which contains measured absorbance values
of Bromide in solution:

> brom
    hours     abs
1    -1.0  0.0633
2     1.0  0.2686
3     5.0  0.2446
4    18.0  0.2274
5    29.0  0.2091
6    42.0  0.1961
7    53.0  0.1310
8    76.0  0.1504
9    91.0  0.1317
10   95.5  0.1169
11  101.0  0.0977
12  115.0  0.1023
13  123.5  0.0879
14  138.5  0.0724
15  147.5  0.0564
16  163.0  0.0495
17  171.0  0.0325
18  189.0  0.0182
19  211.0  0.0047
20  212.5      NA
21  815.5 -0.2112
22  816.5 -0.1896
23  817.5 -0.0783
24  818.5  0.2963
25  819.5  0.1448
26  839.5  0.0936
27  864.0  0.0560
28  888.0  0.0310
29  960.5  0.0056
30 1009.0 -0.0163

The values in column brom$abs, measured on 30 subsequent points in time need
to be calculated to Bromide concentrations, using the previously established
relationship “linear1”.  
At first, I thought it could be done by:

> predict.lm(linear1, brom$abs)
Error in eval(predvars, data, env) : 
  numeric 'envir' arg not of length one

But, R gives the above error message. Then, after some searching around on
different fora and R-communities (including this one), I learned that the
“newdata” in “predict.lm” actually needs to be coerced into a separate
dataframe. Thus:

> mabs <- data.frame(Abs = brom$abs)
> predict.lm(linear1, mabs)
Error in eval(expr, envir, enclos) : object 'conc' not found

Again, R gives an error...probably because I made an error, but I truly fail
to see where. I hope somebody can explain to me clearly what I'm doing wrong
and what I should do to instead.
Any help is greatly appreciated, thanks !

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