Stochastic Profiling using Maximum Likelihood Estimation
![[R logo]](../../../doc/html/Rlogo.svg)
![[Up]](../../../doc/html/left.jpg)
![[Top]](../../../doc/html/up.jpg)
Documentation for package ‘stochprofML’ version 2.0.3
Help Pages
| stochprofML-package | Stochastic Profiling using Maximum Likelihood Estimation |
| analyze.sod2 | Analysis of SOD2 data in stochastic profiling model |
| analyze.toycluster | Analysis of toyclusters in stochastic profiling model |
| calculate.ci.EXPLN | Maximum likelihood confidence intervals for EXP-LN model |
| calculate.ci.LNLN | Maximum likelihood confidence intervals for LN-LN model |
| calculate.ci.rLNLN | Maximum likelihood confidence intervals for rLN-LN model |
| comb.summands | Combinations of fixed number of summands with pre-defined sum. |
| d.sum.of.mixtures.EXPLN | Sums of mixtures of zero, one or more lognormal random variables and one exponential random variable |
| d.sum.of.mixtures.LNLN | Sums of mixtures of lognormal random variables |
| d.sum.of.mixtures.rLNLN | Sums of mixtures of lognormal random variables |
| generate.toydata | Generation and analysis of synthetic data in stochastic profiling model |
| mix.d.sum.of.mixtures.EXPLN | Density of the sum of mixtures of zero, one or more lognormal random variables and one exponential random variable weighted by all possible summands |
| mix.d.sum.of.mixtures.LNLN | Density of the sum of mixtures of lognormal random variables weighted by all possible summands |
| mix.d.sum.of.mixtures.rLNLN | Density of the sum of mixtures of lognormal random variables weighted by all possible summands |
| penalty.constraint.EXPLN | Penalization for population densities that do not fulfil certain constraints for the EXP-LN model |
| penalty.constraint.LNLN | Penalization for population densities that do not fulfil certain constraints for the LN-LN model |
| penalty.constraint.rLNLN | Penalization for population densities that do not fulfil certain constraints for the rLN-LN model |
| r.sum.of.mixtures.EXPLN | Sums of mixtures of zero, one or more lognormal random variables and one exponential random variable |
| r.sum.of.mixtures.LNLN | Sums of mixtures of lognormal random variables |
| r.sum.of.mixtures.rLNLN | Sums of mixtures of lognormal random variables |
| set.model.functions | Defines some global model-dependent functions |
| sod2 | Measurements from the detoxifying enzyme, SOD2 |
| stochasticProfilingData | User prompt for generation and visualization of synthetic data in stochastic profiling model |
| stochasticProfilingML | User prompt for maximum likelihood estimation of stochastic profiling model |
| stochprof.loop | Maximum likelihood estimation for the parameters in the stochastic profiling model |
| stochprof.results.EXPLN | Evaluation of results from estimation of EXP-LN model |
| stochprof.results.LNLN | Evaluation of results from estimation of LN-LN model |
| stochprof.results.rLNLN | Evaluation of results from estimation of rLN-LN model |
| stochprof.search.EXPLN | Calculation of the log likelihood function of the EXP-LN model |
| stochprof.search.LNLN | Calculation of the log likelihood function of the LN-LN model |
| stochprof.search.rLNLN | Calculation of the log likelihood function of the rLN-LN model |
| stochprofML | Stochastic Profiling using Maximum Likelihood Estimation |
| toycluster.EXPLN | Synthetic data from the EXP-LN model |
| toycluster.LNLN | Synthetic data from the LN-LN model |
| toycluster.rLNLN | Synthetic data from the rLN-LN model |