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NAMESPACE: Removed sample,
runif, and setNames from
importFrom(stats, ...). These are base::
functions and are always available without import. Listing them under
stats:: caused the warning:
object 'sample' is not exported by 'namespace:stats' on
devtools::load_all() and R CMD CHECK.
Added correct @importFrom stats coef lm qt sd var
and @importFrom utils head read.csv roxygen2 tags to
R/zzz.R so that devtools::document()
regenerates the NAMESPACE without the base:: /
stats:: confusion.
NRMSampling.Rproj RStudio project file for
streamlined development with devtools,
roxygen2, and testthat integration.stratified_sample() now accepts a named integer vector
for n_per_stratum, enabling Neyman (optimal) or any
user-defined allocation.pps_sample() now attaches .inclusion_prob
(n * p_i) to output, ready for direct use with
ht_estimator().plot_summary() now handles all-numeric data frames when
vars = NULL without requiring explicit column names.carbon_stock_estimate() now validates
carbon_fraction range and documents the IPCC (2006) default
of 0.47.sampling_efficiency() for quantitative comparison
of two sampling designs via relative efficiency (RE = Var1 / Var2).sf or terra are not available, rather than
an opaque error.purposive_sample(): condition evaluation now uses
with() instead of eval(parse(...)) on the
global environment, preventing accidental access to objects outside the
data frame.systematic_sample(): fixed an edge case where
k = nrow(data) would select only one unit rather than
erroring.quota_sample(): now silently caps quota to stratum size
instead of erroring when quota exceeds available units.regression_estimator(): now requires at least 3
complete observations before fitting and raises an informative
error..Rbuildignore updated to exclude
NRMSampling.Rproj and .Rproj.user/ from the
CRAN source bundle..gitignore expanded with comprehensive R, RStudio, and
OS entries.@examples verified to run in under 5
seconds.cran-comments.md updated to reflect v0.2.0 test
environments.srs_sample() – Simple random sampling with/without
replacement.stratified_sample() – Equal, proportional, or Neyman
allocation.systematic_sample() – Fixed-interval systematic
sampling.cluster_sample() – Single-stage cluster sampling.pps_sample() – Probability-proportional-to-size
sampling.convenience_sample() – First-n convenience sample.purposive_sample() – Condition-based purposive
sampling.quota_sample() – Fixed-quota non-random selection.estimate_mean(), estimate_total() – Mean
and total estimators.estimate_variance(), estimate_se() –
Variance and SE with fpc.estimate_ci() – t-based confidence intervals.ratio_estimator() – Ratio estimate of population
total.regression_estimator() – Regression-adjusted mean
estimate.ht_estimator(), ht_variance() –
Horvitz-Thompson estimator and variance.stratified_estimator() – Weighted stratified mean
estimator.biomass_estimate() – Total and mean biomass from plot
data.soil_loss_estimate() – Total and mean soil loss
estimation.carbon_stock_estimate() – Carbon stock from
biomass.plot_summary() – Descriptive statistics for numeric
columns.sampling_efficiency() – Relative efficiency of two
designs.to_sf_points(), spatial_random_sample(),
spatial_systematic_sample(),
spatial_stratified_sample(),
spatial_cluster_sample(),
raster_stratified_sample(),
raster_pps_sample(), extract_raster_values(),
spatial_biomass_estimate(), plot_sampling(),
plot_sampling_gg().sample_nrm – 100-plot synthetic NRM field dataset.sample_spatial – 100-observation geo-referenced NRM
dataset.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.