# sss.point: Draw a Simple Systematic Sample (SSS) from a point resource... In SDraw: Spatially Balanced Sample Draws for Spatial Objects

## Description

Draw a systematic sample from a `SpatialPoints*` object or a `data.frame`. `SpatialPoints*` objects can represent point resources in 2-dimensional space, such as towns, event locations, or grid cell centers.

## Usage

 `1` ```sss.point(x, n) ```

## Arguments

 `x` A `SpatialLines`, `SpatialLinesDataFrame`, or `data.frame` object. `n` Sample size. Number of points to draw from the set of all points in `x`. If `n` exceeds the number of units (= number of rows in `data.frame(x)`), a census is taken (i.e., `x` is returned).

## Details

The points in `x` are systematically sampled in the order they appear. That is, the sampling frame (i.e., `data.frame(x)`) is not re-ordered prior to sampling. Each row in the frame represents a point or sample unit, and rows are sampled systematically starting with row 1. To draw a systematic sample across the range of an attribute, say attribute y, sort `x` by y prior to calling this routine (e.g,. `sss.point( x[order(x\$y),], n )`).

This routine draws fixed size systematic samples. Many systematic sampling procedure produce variable size samples. Conceptually, the sample procedure is:

1. Each sample unit (= row of sample frame) is associated with a line segment. Assuming there are N units in the frame (N = `nrow(x)`), each line segment has length n/N, where n is the input desired sample size.

2. Line segments are placed end-to-end, starting at 0, in the order in which their associated unit appears in the frame.

3. To start the systematic sample, the routine choses a random number between 0 and 1. Let this random number be m.

4. The sample units associated with the line segments containing the numbers m + i for i = 0,1,...,(n-1), are selected for the sample.

## Value

If input `x` inherits from a the `SpatialPointsDataFrame` class, a `SpatialPointsDataFrame` object containing locations in the sample is returned. If input `x` is a `data.frame`, a `data.frame` is returned. Attributes of the returned sample points are:

• `sampleID`: A unique identifier for every sample point. `sampleID` starts with 1 at the first point and increments by one for each.

• If `x` inherits from `SpatialPoints`, returned points have attribute `geometryID` – the ID (=`row.names(x)`) of the sampled point.

• Any attributes (columns) associated with the input points (rows).

Additional attributes of the output object are:

• `frame`: Name of the input sampling frame (i.e., `x`).

• `frame.type`: Type of resource in sampling frame. (i.e., "point").

• `sample.type`: Type of sample drawn. (i.e., "SSS").

• `random.start`: The random start for the systematic sample.

Using these additional attributes, one could reconstruct the sample.

## Author(s)

Trent McDonald

`sss.polygon`, `sss.line`, `sdraw`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```# Draw systematic sample across range of population WA.samp <- sss.point( WA.cities[order(WA.cities\$POP_2010),], 100 ) plot( WA.cities ) points( WA.samp, col="red", pch=16 ) # Draw systematic sample from data frame df <- data.frame( a=1:100, b=runif(100) ) samp <- sss.point( df, 5 ) # Equivalent to simple random sample: randomly sort frame. samp <- sss.point( df[order(df\$b),], 5 ) ```

SDraw documentation built on May 29, 2017, 6:14 p.m.