Man pages for statsmaths/smodels
Consistent format for fitting models
| ConfInt | Confidence interval summaries |
| QuantileSummary | Quantile summaries |
| SingleSummary | Numeric Summaries |
| sm_check_download | Check if a local file exists and otherwise download it |
| sm_dunn_ll | Compute Dunn Likelihood scores |
| sm_graph_layout | Add network metadata and layout information |
| sm_graph_metadata | Add network metadata to edge and node lists |
| sm_kmeans | Create a data frame of Kmeans clusters |
| sm_kwic | Keywords in Context |
| sm_lda_topics | Compute Tidy LDA Topic Model |
| sm_ngram | N-Grams |
| sm_skip_ngram | Skip N-Grams |
| sm_spectral_cluster | Create a data frame of Kmeans clusters |
| sm_text_tfidf | Construct the TF-IDF Matrix from Annotation or Data Frame |
| sm_tidy_angle_distance | Create a data frame of pairwise Cosine similarities |
| sm_tidy_distance | Create a data frame of pairwise (Euclidiean) distances |
| sm_tidy_glmnet | Create a data frame of elastic net coefficents |
| sm_tidy_matrix | Tidy a Matrix Object |
| sm_tidy_pca | Create a data frame of principal components |
| sm_tidy_umap | Create a data frame of umap components |
| sm_to_pixel | Unravel Nested Dataset of Images into Pixels |
| theme_sm | Minimal theme perfect for presentations |
