Response surface designs with neighbour effects are suitable for experimental situations 
            where it is expected that the treatment combination administered to one experimental unit 
            may affect the response on neighboring units as well as the response on the unit to which it is applied. 
            Integrating these effects in the response surface model improves the experiment's precision 
            (Jaggi, S., Sarika and Sharma, V.K. (2010)<http://krishi.icar.gov.in/jspui/handle/123456789/4364>; 
            Verma A., Jaggi S., Varghese, E.,Varghese, C.,Bhowmik, A., Datta, A. and Hemavathi M. (2021)<DOI: 10.1080/03610918.2021.1890123>). 
            This package includes sym(), asym1(), asym2() functions that generates response surface designs which are rotatable under a 
            polynomial model of a given order without interaction term incorporating neighbour effects.

A Bayesian-weighted estimator and two unweighted estimators are
 developed to estimate the number of newly found rare species in additional
 ecological samples. Among these methods, the Bayesian-weighted estimator
 and an unweighted (Chao-derived) estimator are of high accuracy and
 recommended for practical applications.
 Technical details of the proposed estimators have been well described
 in the following paper: Shen TJ, Chen YH (2018) A Bayesian
 weighted approach to predicting the number of newly discovered
 rare species. Conservation Biology, In press.

SEA performs simultaneous feature-set testing for (gen)omics data. It tests the unified null hypothesis controls the family-wise error rate for all possible pathways. The unified null hypothesis is defined as: "The proportion of true features in the set is less than or equal to the threshold c", where c is selected by the user. Family-wise error rate control is provided through use of closed testing with Simes test. For more information on closed testing with Simes see Goeman et al. (2019) <doi:10.1093/biomet/asz041> and for more information about the properties and performance of SEA procedure see Ebrahimpoor et al. (2019) <doi:10.1093/bib/bbz074>.