Density, probability, quantile and random number
        generation functions for the truncated normal distribution.

Finds the posterior modes for the mean and standard deviation for a
  truncated normal distribution with one or two known truncation points.
  The method used extends Bayesian methods for parameter estimation for a singly
  truncated normal distribution under the Jeffreys prior (see Zhou X,
  Giacometti R, Fabozzi FJ, Tucker AH (2014). "Bayesian estimation of truncated
  data with applications to operational risk measurement".
  <doi:10.1080/14697688.2012.752103>). This package additionally allows for a
  doubly truncated normal distribution.

Estimation of models for truncated Gaussian variables by maximum likelihood.

Semi-parametric estimation of truncated linear regression models

Does local optimization using two derivatives and trust regions.
    Guaranteed to converge to local minimum of objective function.

Trusted Timestamps (tts) are created by incorporating a hash of a file or dataset into a transaction on the decentralized blockchain (Stellar network). 
    The package makes use of a free service provided by <https://stellarapi.io>.

Trust region algorithm for nonlinear optimization. Efficient when
    the Hessian of the objective function is sparse (i.e., relatively few nonzero
    cross-partial derivatives). See Braun, M. (2014) <doi:10.18637/jss.v060.i04>.

Advanced tryCatch() and try() functions for better error handling
             (logging, stack trace with source code references and support for post-mortem analysis via dump files).

Differentiate client errors (4xx)
  from server errors (5xx) for the 'plumber' and 
  'RestRserve' HTTP API frameworks. The package
  also includes a built-in logging mechanism
  to standard output (STDOUT) or standard error
  (STDERR) depending on the log level.

Contains R functions and datasets detailed in the book
        "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.