Package: anumaan 0.1.0.9036

Overview | Resistance Profile Estimation | Option 1: Convex Optimisation (Pathway 1) | 1.1 Aggregate Input: Validate Marginals | 1.2 Profile Enumeration | 1.3 Constraint Matrix | 1.4 Estimate Profile Probabilities | 1.5 Facility Line-List Pathway | 1.6 Check Constraint Satisfaction | 1.7 Bootstrap Uncertainty Intervals | Option 2: Bayesian Multivariate Probit (Pathway 2) | 2.1 Prepare Event-Level Class Data | 2.2 Fit the Model | 2.3 Convert Posterior Draws to Resistance-Profile Probabilities | 2.4 Aggregate for DALY | 2.5 Validate Calibration | 2.6 Predictive Checks | 2.7 Unified Dispatcher | 2.8 Post-Fit Checklist: What to Run, and Why | Pipeline at a Glance | Session Info

What is anumaan? | Pipeline 1 — Preprocessing | Pipeline 2 — Exploratory Data Analysis | Pipeline 3 — DALY Burden Estimation | Bayesian multivariate probit backend selection | Installation | Optional dependencies | Data Format | Package Reference

Overview | Connecting from Pipeline 1 | A Small Synthetic Dataset | Theme | Organism and Susceptibility Overview | Top organisms | Susceptibility pattern (stacked R/S bars) | Resistance heatmap | Resistance by specimen type | Resistance by age bin and by organism | Outcomes | Overall distribution | Outcome by organism, split by resistance status | Death vs. discharged | Outcome by age bin and by year | Case-Mix and Facility Patterns | Patients per hospital | Monomicrobial vs. polymicrobial, by facility | HAI vs. CAI, by facility | Location (ICU vs. Ward), by facility | Infection type by location | Syndrome distribution | Length of Stay and Age Distributions | LOS ridge plot | Age ridge plot | LOS by age bin | Pipeline at a Glance | Summary | Session Info

Overview | A Small Synthetic Raw Dataset | Schema Checks and Column Mapping | Inspect what preprocessing is possible | Build a rename map explicitly | One-step convenience wrapper | Assert the minimum standard names | Dates and Table Validation | Parse a single vector of mixed date encodings | Validate and coerce the working table | Validate chronology | Standardize Core Clinical Fields | Organisms | Specimen, sex, outcome, and infection type | Antibiotics and AST values | Demographic and Clinical Derivations | Fill age and assign age bins | Derive length of stay | Derive HAI/CAI and source flags | Assign facility type | Event Creation and AST Reshaping | Create event IDs from long-format isolates | Deduplicate event-level rows | Classify readmissions from admission dates | Standardize non-conforming readmission labels | Pivot wide AST input to long format | Deduplicate AST records | MDR/XDR Classification | Collapse to class level | Classify MDR/XDR | Contaminants and Polymicrobial Episodes | Flag likely contaminants | Exclude fungal isolates when needed | Flag and weight polymicrobial episodes | Attrition and Analysis Readiness | Track attrition across preprocessing stages | Final readiness checks | Summary