esttimateR: use bias-corrected Chao1 only when doubletons = 0

Previously we always used bias-corrected form of Chao1, but
it seems that the normal biased form should normally be used, and
only when it cannot be estimated (because we divide by the number
of doubletons).

The sd of bias-corrected form is made NA in this commit: fixed in
the next one.
Chao1 got small-sample correction and bias-corrected variance

estimateR upgrade following Chun et al., Biometrics 70, 671-682
(2014). Now the behaviour should be similar as in EstimateS, but
the variance formulae differ (our based on the cited publication).
Chao index in specpool got small-sample correction and bias-correction
Finally complete eq. for variance of extrapolated bootstrap richness
Update vignettes to the update Chao richness estimators
Use always bias-corrected form in Chao1 of estimateR
update man/ pages for upgraded Chao richness
proof-read and format man/specpool.Rd
Proof-read equations in updated Chao documentation
Forgot to take the sd of variance in estimateR
Use EstimateS formula (eq6) for the variance

The EstimateS web page eq6 formula is actually incorrect: it is
derived on the partial derivatives of classic Chao, but the terms
of the final result are replaced with the terms of bias-corrected
Chao. However, numerically the error is only about 1% of the correct
form and therefore we resent to use this widespread approximation.
fix small sample correction of var(Chao) when there are no doubletons

I reconstructed the variance formula (3b) of Chiu et al. 2014 using
the procedure described in their online appendix. I could get the same
formula except for the small-sample correction: it seems that EstimateS
web page got this correctly, but Chiu et al. ignore the small-sample
correction for all but the first term.
Update diversity vignette for the current state of Chao estimates
Make small sample correction optional in specpool
estimateR will not use small sample correction

In addition, clarify man/ page for estimateR
sync poolaccum with Chao changes in specpool

* switch to bias-corrected Chao when a2==0
* use small-sample correction in Chao (hard-wired)
Merge pull request #67 from jarioksa/chao

Chao equations