This framework aims to provide classes and methods for manipulating and processing of raster time series data (e.g. a time series of satellite images).

Supports modelling real-time case data to facilitate the real-time
    surveillance of infectious diseases and other point phenomena. The package provides automated computational grid generation over
    an area of interest with methods to map covariates between geographies, model fitting including spatially aggregated case counts, 
    and predictions and visualisation. Both Bayesian and maximum likelihood methods are provided. Log-Gaussian Cox Processes are described by 
    Diggle et al. (2013) <doi:10.1214/13-STS441> and we provide both the low-rank approximation for Gaussian processes 
    described by Solin and Särkkä (2020) <doi:10.1007/s11222-019-09886-w> and Riutort-Mayol et al (2020) <arXiv:2004.11408> and the
    nearest neighbour Gaussian process described by Datta et al (2016) <doi:10.1080/01621459.2015.1044091>. 'cmdstanr' can be downloaded at <https://mc-stan.org/cmdstanr/>.

Frequentist sequential meta-analysis based on 
    'Trial Sequential Analysis' (TSA) in programmed in Java by the Copenhagen 
    Trial Unit (CTU). The primary function is the calculation of group 
    sequential designs for meta-analysis to be used for planning and analysis of
    both prospective and retrospective sequential meta-analyses to preserve 
    type-I-error control under sequential testing. 'RTSA' includes tools for 
    sample size and trial size calculation for meta-analysis and core 
    meta-analyses methods such as fixed-effect and random-effects models and
    forest plots. TSA is described in Wetterslev et. al (2008) 
    <doi:10.1016/j.jclinepi.2007.03.013>. The methods for deriving the
    group sequential designs are based on Jennison and Turnbull (1999,
    ISBN:9780849303166).

A tool that allows to download and save historical time series data 
	for future use offline. The intelligent updating functionality will only download 
	the new available information; thus, saving you time and Internet bandwidth. 
	It will only re-download the full data-set if any inconsistencies are detected. 
	This package supports following data provides: 'Yahoo' (finance.yahoo.com), 
	'FRED' (fred.stlouisfed.org), 'Quandl' (data.nasdaq.com), 
	'AlphaVantage' (www.alphavantage.co), 'Tiingo' (www.tiingo.com).