[Macosso]

This pull request adds major new features and improvements to the cross-sectional dependence diagnostics in the csdm package. The most significant update is the extension of the cd_test() function to support direct testing of panel variables from data.frame and pdata.frame objects, not just residuals or fitted models. The update also introduces a reps parameter for repeated randomization in CDw/CDw+ tests, improves reporting of excluded time periods, and provides clearer documentation and print output.

New and extended methods for panel variable testing:

• Added cd_test() methods for data.frame and pdata.frame objects, allowing users to select numeric panel variables explicitly via ... (bare names, quoted names, or character vectors). These methods require explicit id and time columns for plain data frames and use stored indexes for pdata.frame. The results are returned as a named list (cd_test_list), with one result per variable, and print as a combined table with sample dimensions. [1] [2] [3] [4]

Enhancements to CDw and CDw+ tests:

• Introduced a reps argument to CDw and CDw+ tests, allowing multiple independent random weight draws (default 1). The statistics are combined according to equation (33) of Juodis and Reese, and the number of draws is recorded in the output. Seeded calls now apply the seed separately to each variable's test. [1] [2] [3] [4] [5] [6]

Improved reporting and print output:

• The print method for cd_test_list now displays a combined table of results by variable, including test statistics, p-values, and sample dimensions. [1] [2]

Handling of incomplete time periods:

• The function now records incomplete time periods removed by drop.incomplete.times in an excluded_times field, alongside periods with no finite observations, for more transparent reporting. [1] [2] [3]

Documentation and usage examples:

• Expanded documentation in both Roxygen and README.md to reflect the new methods, argument details, and usage examples for variable selection and repeated randomization. [1] [2] [3] [4] [5] [6]

These changes make the cross-sectional dependence diagnostics more flexible, user-friendly, and informative for a wider range of panel data workflows.

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Codecov Report

❌ Patch coverage is 94.54545% with 9 lines in your changes missing coverage. Please review.
✅ Project coverage is 84.91%. Comparing base (e562783) to head (fa9085a).

Files with missing lines	Patch %	Lines
R/utils_cd.R	89.18%	8 Missing ⚠️
R/utils_cd_data.R	98.90%	1 Missing ⚠️
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Additional details and impacted files

@@            Coverage Diff             @@
##           master      #14      +/-   ##
==========================================
+ Coverage   82.93%   84.91%   +1.98%     
==========================================
  Files          16       17       +1     
  Lines        1365     1518     +153     
==========================================
+ Hits         1132     1289     +157     
+ Misses        233      229       -4     

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