code: def example_n():
      print(
          skewnorm.pdf(1, 0),
          stats.norm.pdf(1),
          skewnorm.pdf(1, 0) - stats.norm.pdf(1),
      )
      print(
          skewnorm.pdf(1, 1000),
          stats.chi.pdf(1, 1),
          skewnorm.pdf(1, 1000) - stats.chi.pdf(1, 1),
      )
      print(
          skewnorm.pdf(-1, -1000),
          stats.chi.pdf(1, 1),
          skewnorm.pdf(-1, -1000) - stats.chi.pdf(1, 1),
      )
      rvs = skewnorm.rvs(0, size=500)
      print("sample mean var: ", rvs.mean(), rvs.var())
      print("theoretical mean var", skewnorm.stats(0))
      rvs = skewnorm.rvs(5, size=500)
      print("sample mean var: ", rvs.mean(), rvs.var())
      print("theoretical mean var", skewnorm.stats(5))
      print(
          skewnorm.cdf(1, 0),
          stats.norm.cdf(1),
          skewnorm.cdf(1, 0) - stats.norm.cdf(1),
      )
      print(
          skewnorm.cdf(1, 1000),
          stats.chi.cdf(1, 1),
          skewnorm.cdf(1, 1000) - stats.chi.cdf(1, 1),
      )
      print(
          skewnorm.sf(0.05, 1000),
          stats.chi.sf(0.05, 1),
          skewnorm.sf(0.05, 1000) - stats.chi.sf(0.05, 1),
      )
  
file_path: statsmodels/statsmodels/sandbox/distributions/examples/ex_extras.py
imports: import numpy
  from scipy import stats
  from statsmodels.sandbox.distributions.extras import SkewNorm_gen, skewnorm, ACSkewT_gen, NormExpan_gen, pdf_moments, ExpTransf_gen, LogTransf_gen
  from statsmodels.stats.moment_helpers import mc2mvsk, mnc2mc, mvsk2mnc
label_desc: Use image node_id 1 for calling a global function with example usage: example_n() without return types