Gives something like this:
Exact binomial test
data: c(1003, 1014)
number of successes = 1003, number of trials = 2017, pvalue = 0.4119
alternative hypothesis: true probability of success is less than 0.5
95 percent confidence interval:
0.0000000 0.5158274
sample estimates:
probability of success
0.4972732


Sign Test
R does not have a separate sign test, but it can be carried out by first eliminating ties and then using the exact
binomial test.

Gives something like this:
Exact binomial test
data: c(7, 1)
number of successes = 7, number of trials = 8, pvalue = 0.03516
alternative hypothesis: true probability of success is greater than 0.5
95 percent confidence interval:
0.5293206 1.0000000
sample estimates:
probability of success
0.875


Gives something like this:
McNemar's Chisquared test with continuity correction
data: tab1
McNemar's chisquared = 34.3, df = 1, pvalue = 4.724e09


Cox & Stuart test for trend

Gives something like this:
Exact binomial test
data: c(4, 0)
number of successes = 4, number of trials = 4, pvalue = 0.125
alternative hypothesis: true probability of success is not equal to 0.5
95 percent confidence interval:
0.3976354 1.0000000
sample estimates:
probability of success
1


There is as yet no provision in the package epitools in R for estimating the confidence interval to the difference between paired proportions.