* Access Domains and Search Popular Websites* (

**websearchr**)

Functions that allow for accessing domains and a number of search engines.

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**Hyphenation and Syllable Counting for Text Analysis****sylly**)

Provides the hyphenation algorithm used for ‘TeX’/’LaTeX’ and similar software, as proposed by Liang (1983, <https://…/> ). Mainly contains the function hyphen() to be used for hyphenation/syllable counting of text objects. It was originally developed for and part of the ‘koRpus’ package, but later released as a separate package so it’s lighter to have this particular functionality available for other packages. Support for various languages needs be added on-the-fly or by plugin packages; this package does not include any language specific data. Due to some restrictions on CRAN, the full package sources are only available from the project homepage. To ask for help, report bugs, request features, or discuss the development of the package, please subscribe to the koRpus-dev mailing list (<http://korpusml.reaktanz.de> ).

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**Optimal Design and Statistical Power of Cost-Efficient Multilevel Randomized Trials****odr**)

Calculate the optimal sample allocation that minimizes variance of treatment effect in a multilevel randomized trial under fixed budget and cost structure, perform power analyses with and without accommodating costs and budget. The reference for proposed methods is: Shen, Z., & Kelcey, B. (under review). Optimal design of cluster randomized trials under condition- and unit-specific cost structures. 2018 American Educational Research Association (AERA) annual conference.

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**Fit and Predict a Gaussian Process Model with (Time-Series) Binary Response****binaryGP**)

Allows the estimation and prediction for binary Gaussian process model. The mean function can be assumed to have time-series structure. The estimation methods for the unknown parameters are based on penalized quasi-likelihood/penalized quasi-partial likelihood and restricted maximum likelihood. The predicted probability and its confidence interval are computed by Metropolis-Hastings algorithm. More details can be seen in Sung et al (2017) <arXiv:1705.02511>.

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**Distributions and Gradients****dng**)

Provides density, distribution function, quantile function and random generation for the split-t distribution, and computes the mean, variance, skewness and kurtosis for the split-t distribution (Li, F, Villani, M. and Kohn, R. (2010) <doi:10.1016/j.jspi.2010.04.031>).

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**Simulation Based Inference of Lasso Estimator****EAinference**)

Estimator augmentation methods for statistical inference on high-dimensional data, as described in Zhou, Q. (2014) <doi:10.1080/01621459.2014.946035> and Zhou, Q. and Min, S. (2017) <doi:10.1214/17-EJS1309>. It provides several simulation-based inference methods: (a) Gaussian and wild multiplier bootstrap for lasso, group lasso, scaled lasso, scaled group lasso and their de-biased estimators, (b) importance sampler for approximating p-values in these methods, (c) Markov chain Monte Carlo lasso sampler with applications in post-selection inference.