v 4.4

1. Include PM10 pollution data set and its square root transformation
2. Include multivariate time series method for forecasting principal component scores, called farforecast
3. Include a stationarity test, called T_stationary, for functional time series 
4. Update forecast.ftsm function (ftsa:::ftsmPI)

v 4.3

1. Remove R2jags package dependency and put it as a suggested package

v 4.2

1. Update dynupdate function
2. Update ftsm function
3. Update fdpca function
4. Update plsPI function
5. Add MFDM function

v 4.1

1. Add pcaPP and MASS packages as imports
2. Remove \donttest in the examples
3. Add \alias{ftsa} in the ftsa-package help file

v 4.0

1. Update the ftsm and forecast.ftsm functions for handling functional time series

v 3.9

1. Update the plot.ftsf function
2. Add Imports field in the description file

v 3.8

1. Update the ftsa:::fdpca function
2. Update the ftsm function
3. Update the plot.ftsm function

v 3.7

1. Update the forecast.ftsm function
2. Update the forecast.ftsm2 function

v 3.6

1. Add more detail to the example section
2. Add the depth.radius option to the mean.fts, median.fts, sd.fts and var.fts

v 3.5

1. Update the plot.fmres function using the colorspace package
2. Delete some internal functions, namely cm.spline.R, KalmanLike.R, L1median.R, PCAproj.R, ash2.R, bin2.R

v 3.4

1. Update the ftsm function
2. Update the var.default function
3. Update the ftsa:::plsPI function
4. Add the vignette

v 3.3

1. Update the sd.default.R, var.default.R functions.

v 3.2

1. Delete the standard sd.R, var.R, quantile.R, median.R functions, which are available in base

v 3.1

1. Update the scaled error measures in the error function

v 3.0

1. Correct the plot.ftsm function
2. Update plot.ftsf function

v 2.9

1. Correct the plot.ftsm function

v 2.8

1. Update the plot.ftsm function
2. Add the forecast.fplsr function
3. Add the forecast.ftsmiterative function
4. Add the plot.fplsr function
5. Add the pcscorebootstrapdata function

v 2.7

1. Update the extract function
2. Add the ftsmweightselect function to select the optimal weighted used in the weighted ftsm

v 2.6

1. Update ftsm function to produce the orthonormal basis functions

v 2.5 

1. correct ftsm function 

v 2.4

1. correct ftsm function weight

v 2.3

1. correct ftsm function

v 2.2 

1. correct ftsm function

v 2.1

1. update ftsm 
2. update mean.fts and median.fts

v 2.0

1. update plot.ftsm
2. add varprop output in ftsm function when weight = TRUE

v 1.9

1. Remove some duplicate functions

v 1.8

1. Update the arfima function in forecast.ftsm

v 1.7

1. Change the package dependency of fds
2. Update the forecast.ftsm() function (allowing struct and arfima models, and fixing the way stationary models are used)
3. Update the isfe.fts() function (adding ar and arfima as possible forecast methods)
4. Make plot.ftsm visible
5. Update plot.ftsm to allow plotting specific components

v 1.6

1. Update the JCGS reference

v 1.5

1. Update the ftsa:::me function
2. Add the ftsa:::mpe function

v 1.4

1. Update dynupdate function to incorporate three ways of computing functional principal component analysis.

v 1.3

1. Add dynupdatelambdaselect function. 

v 1.2

1. Correct the extract function
2. Add ftsmweightselect and fplsrweightselect functions to determine geometrically decaying weights

v 1.1

1. Update the references
2. Correct the yname of a functional object