psmat {collapse}

Matrix / Array from Panel Series

Description

psmat efficiently expands a panel-vector or 'indexed_series' ('pseries') into a matrix. If a data frame or 'indexed_frame' ('pdata.frame') is passed, psmat returns a 3D array or a list of matrices.

Usage

psmat(x, ...)

## Default S3 method:
psmat(x, g, t = NULL, transpose = FALSE, ...)

## S3 method for class 'data.frame'
psmat(x, by, t = NULL, cols = NULL, transpose = FALSE, array = TRUE, ...)

# Methods for indexed data / compatibility with plm:

## S3 method for class 'pseries'
psmat(x, transpose = FALSE, drop.index.levels = "none", ...)

## S3 method for class 'pdata.frame'
psmat(x, cols = NULL, transpose = FALSE, array = TRUE, drop.index.levels = "none", ...)


## S3 method for class 'psmat'
plot(x, legend = FALSE, colours = legend, labs = NULL, grid = FALSE, ...)

Arguments

x

a vector, indexed series 'indexed_series' ('pseries'), data frame or 'indexed_frame' ('pdata.frame').

g

a factor, GRP object, atomic vector (internally converted to factor) or a list of vectors / factors (internally converted to a GRP object) used to group x. If the panel is balanced an integer indicating the number of groups can also be supplied. See Examples.

by

data.frame method: Same input as g, but also allows one- or two-sided formulas using the variables in x, i.e. ~ idvar or var1 + var2 ~ idvar1 + idvar2.

t

same inputs as g/by, to indicate the time-variable(s) or second identifier(s). g and t together should fully identify the panel. If t = NULL, the data is assumed sorted and seq_col is used to generate rownames for the output matrix.

cols

data.frame method: Select columns using a function, column names, indices or a logical vector. Note: cols is ignored if a two-sided formula is passed to by.

transpose

logical. TRUE generates the matrix such that g/by -> columns, t -> rows. Default is g/by -> rows, t -> columns.

array

data.frame / pdata.frame methods: logical. TRUE returns a 3D array (if just one column is selected a matrix is returned). FALSE returns a list of matrices.

drop.index.levels

character. Either "id", "time", "all" or "none". See indexing.

...

arguments to be passed to or from other methods, or for the plot method additional arguments passed to ts.plot.

legend

logical. Automatically create a legend of panel-groups.

colours

either TRUE to automatically colour by panel-groups using rainbow or a character vector of colours matching the number of panel-groups (series).

labs

character. Provide a character-vector of variable labels / series titles when plotting an array.

grid

logical. Calls grid to draw gridlines on the plot.

Details

If n > 2 index variables are attached to an indexed series or frame, the first n-1 variables in the index are interacted.

Value

A matrix or 3D array containing the data in x, where by default the rows constitute the groups-ids (g/by) and the columns the time variable or individual ids (t). 3D arrays contain the variables in the 3rd dimension. The objects have a class 'psmat', and also a 'transpose' attribute indicating whether transpose = TRUE.

Note

The pdata.frame method only works for properly subsetted objects of class 'pdata.frame'. A list of 'pseries' won't work. There also exist simple aperm and [ (subset) methods for 'psmat' objects. These differ from the default methods only by keeping the class and the 'transpose' attribute.

See Also

Time Series and Panel Series, Collapse Overview

Examples

## World Development Panel Data
head(wlddev)                                                    # View data
qsu(wlddev, pid = ~ iso3c, cols = 9:12, vlabels = TRUE)         # Sumarizing data
str(psmat(wlddev$PCGDP, wlddev$iso3c, wlddev$year))             # Generating matrix of GDP
r <- psmat(wlddev, PCGDP ~ iso3c, ~ year)                       # Same thing using data.frame method
plot(r, main = vlabels(wlddev)[9], xlab = "Year")               # Plot the matrix
str(r)                                                          # See srructure
str(psmat(wlddev$PCGDP, wlddev$iso3c))                          # The Data is sorted, could omit t
str(psmat(wlddev$PCGDP, 216))                                   # This panel is also balanced, so
# ..indicating the number of groups would be sufficient to obtain a matrix

ar <- psmat(wlddev, ~ iso3c, ~ year, 9:12)                      # Get array of transposed matrices
str(ar)
plot(ar)
plot(ar, legend = TRUE)
plot(psmat(collap(wlddev, ~region+year, cols = 9:12),           # More legible and fancy plot
           ~region, ~year), legend = TRUE,
     labs = vlabels(wlddev)[9:12])

psml <- psmat(wlddev, ~ iso3c, ~ year, 9:12, array = FALSE)     # This gives list of ps-matrices
head(unlist2d(psml, "Variable", "Country", id.factor = TRUE),2) # Using unlist2d, can generate DF

## Indexing simplifies things
wldi <- findex_by(wlddev, iso3c, year)  # Creating an indexed frame
PCGDP <- wldi$PCGDP                     # An indexed_series of GDP per Capita
head(psmat(PCGDP), 2)                   # Same as above, more parsimonious
plot(psmat(PCGDP))
plot(psmat(wldi[9:12]))
plot(psmat(G(wldi[9:12])))              # Here plotting panel-growth rates