Price volatility refers to the degree of variation in series over a certain period of time. This volatility is especially noticeable in agricultural commodities, adding uncertainty for farmers, traders, and others in the agricultural supply chain. Commonly and popularly used four volatility models viz, GARCH, Glosten Jagannatan Runkle-GARCH (GJR-GARCH) model, exponentially weighted moving average (EWMA) model and Multiplicative Error Model (MEM) are selected and implemented. PWAVE, weighted ensemble model based on particle swarm optimization (PSO) is proposed to combine the forecast obtained from all the candidate models. This package has been developed using algorithm of Paul et al. <doi:10.1007/s40009-023-01218-x> and Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>.

Build piecewise exponential survival model for study design (planning) and event/timeline prediction.

A function 'PWI()' that calculates prize winner indices based on bibliometric data is provided. The default is the 'Derek de Solla Price Memorial Medal'. Users can provide recipients of other prizes.

Estimates two-level multilevel linear model and two-level multivariate linear multilevel model with weights following Probability Weighted Iterative Generalised Least Squares approach. For details see Veiga et al.(2014) <doi:10.1111/rssc.12020>.

Power analysis functions along the lines of Cohen (1988).

User friendly functions for power and sample size analysis at one-way and two-way ANOVA settings take either effect size or delta and sigma as arguments. They are designed for both one-way and two-way ANOVA settings. In addition, a function for plotting power curves is available for power comparison, which can be easily visualized by statisticians and clinical researchers.

Statistical power analysis for designs including t-tests, correlations, 
    multiple regression, ANOVA, mediation, and logistic regression. Functions accompany 
    Aberson (2019) <doi:10.4324/9781315171500>.

Power analysis for AB testing. The calculations are based on the Welch's unequal variances t-test,
  which is generally preferred over the Student's t-test when sample sizes and variances of the two groups are
  unequal, which is frequently the case in AB testing. In such situations, the Student's t-test will give 
  biased results due to using the pooled standard deviation, unlike the Welch's t-test.