Package index
- 
          prepare_data()
- Prepare data - Step 1
- 
          process_data()
- Process data - Step 2
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          process_nquire()
- Use nQuire's Data
- 
          denoise_data()
- Denoise Data
- 
          Bclean()
- Remove noise with the beta distribution
- 
          sim.ind.BB()
- Simulate Allele Counts for Single Individual - Beta-Binomial Distribution
- 
          sim.ind.BB.tau()
- Simulate Allele Counts for Single Individual - Beta-Binomial Distribution with Overdispersion and Error
- 
          sim.ind.simple()
- Simulate Allele Counts for Single Individual - Simple Approach
Basic Mixture Models
Wrapper functions to run model selection for diploids, triploids, tetraploids, pentaploids, and hexaploids.
- 
          quackNormal()
- Model Selection - Expectation Maximization - Normal Mixture
- 
          quackNormalNQ()
- Model Selection - Expectation Maximization - Normal Mixture (nQuire)
- 
          quackBeta()
- Model Selection - Expectation Maximization - Beta Mixture
- 
          quackBetaBinom()
- Model Selection - Expectation Maximization - Beta-Binomial Mixture
More on Mixture Models
Wrapper functions for model selection, running specific sets of mixture models, and bootstrap replication.
- 
          quackit()
- Model Selection - Based on BIC or Log-Likelihood
- 
          bestquack()
- Model Selection - Expectation Maximization - Choose your distribution and type
- 
          quackNboots()
- Bootstrapping - Expectation Maximization - Choose your distribution and type
- 
          emstepN()
- Expectation maximization - Normal Distribution
- 
          emstepNU()
- Expectation maximization - Normal and Uniform Distribution
- 
          emstepNA()
- Expectation maximization - Normal Distribution
- 
          emstepNUA()
- Expectation maximization - Normal Distribution
- 
          emstepB()
- Expectation maximization - Beta Distribution
- 
          emstepBU()
- Expectation maximization - Beta and Uniform Distributions
- 
          emstepBB()
- Expectation maximization - Beta-Binomial Distribution
- 
          emstepBBU()
- Expectation maximization - Beta-Binomial and Uniform Distributions
- 
          estepB3()
- E-Step for Expectation Maximization - Beta + Beta + Beta Distribution
- 
          emstepB3()
- Expectation maximization - Beta + Beta + Beta Distribution
- 
          alphabetacalc()
- Calculate Alpha and Beta from Mean and Variance
- 
          alphabetacalctau()
- Calculate Alpha and Beta from Mean, Tau, and Error rate.
- 
          alphabetacalcvec()
- Vector-based - Calculate Alpha and Beta from Mean and Variance
- 
          alphabetacalctauvec()
- Vector-based - Calculate Alpha and Beta from Mean, Tau, and Error rate.
- 
          muvarcalcvec()
- Variance calculation from Mean, Tau, and Sequencing Error
- 
          process_rcpp()
- Data Preparation - Matrix Filtering
- 
          nQuire_reformat()
- Data Preparation - Use nQuire's Data
- 
          setconvert()
- Calculate Variance from Mean, Tau, and Sequencing Error
- 
          resample_xm()
- Calculate Alpha and Beta from Mean and Variance