*way*cool, is incidental to this post.) It was a favor for a friend, something she intends to use teaching an online course. Two of the tasks, while fairly mundane, generated code that was just barely obscure enough to be possibly worth sharing. It's straight R code, so you need not use (or have installed) Shiny to use it.

The first task was to output, in tabular form, the coefficients of a linear regression model, along with their respective confidence intervals. The second task was to output, again in tabular form, the fitted values, confidence intervals and prediction intervals for the same model. Here is the function I wrote to do the first task (with Roxygen comments):

To demonstrate its operation, I'll generate a small sample with random data and run a linear regression on it.

I'll generate the coefficient table using confidence level 0.9, rather than the default 0.95, for the coefficients.

model.ctable(m, level = 0.9)

Estimate Std. Error t value Pr(>|t|) 5 % 95 % (Intercept) 6.039951 0.2285568 26.42648 3.022477e-15 5.642352 6.437550 x 3.615331 0.2532292 14.27691 6.763279e-11 3.174812 4.055850 y -5.442428 0.3072587 -17.71285 2.156161e-12 -5.976937 -4.907918

The code for the second table (fits, confidence intervals and prediction intervals) is a bit longer:

Here is the call with default arguments (using head() to limit the amount of output):

The output is this:

PI Low CI Low Fitted CI High PI High 1 -0.7928115 0.65769280 1.5196870 2.381681 3.832185 2 7.9056270 9.40123642 10.1928094 10.984382 12.479992 3 4.9125024 6.61897662 7.1149000 7.610823 9.317298 4 7.3386447 8.66123993 9.7406923 10.820145 12.142740 5 -1.4295587 0.05464529 0.8637503 1.672855 3.157059 6 4.1962493 5.84893725 6.4156619 6.982387 8.635074Finally, I'll run it again, changing the confidence level to 0.9, tweaking the column headings a bit, and reordering them:

The output is:

Fit CI_l CI_u PI_l PI_u 1 1.5196870 0.8089467 2.230427 -0.3870379 3.426412 2 10.1928094 9.5401335 10.845485 8.3069584 12.078660 3 7.1149000 6.7059962 7.523804 5.2989566 8.930843 4 9.7406923 8.8506512 10.630733 7.7601314 11.721253 5 0.8637503 0.1966188 1.530882 -1.0271523 2.754653 6 6.4156619 5.9483803 6.882943 4.5856891 8.245635By the way, all syntax highlighting was Created by Pretty R at inside-R.org.

## No comments:

## Post a Comment

Due to intermittent spamming, comments are being moderated. If this is your first time commenting on the blog, please read the Ground Rules for Comments. In particular, if you want to ask an operations research-related question not relevant to this post, consider asking it on Operations Research Stack Exchange.