Here is a list of all data types members with links to the data types they belong to:

- p -

• P : gpmp::nt::RC5
• pack_buffer_A() : gpmp::linalg::DGEMM , gpmp::linalg::IGEMM , gpmp::linalg::SGEMM
• pack_buffer_B() : gpmp::linalg::DGEMM , gpmp::linalg::IGEMM , gpmp::linalg::SGEMM
• pack_micro_A() : gpmp::linalg::DGEMM , gpmp::linalg::IGEMM , gpmp::linalg::SGEMM
• pack_micro_B() : gpmp::linalg::DGEMM , gpmp::linalg::IGEMM , gpmp::linalg::SGEMM
• partial_corr() : gpmp::stats::Describe
• partition_distinct() : gpmp::Comb
• partitions() : gpmp::Comb
• penalty_type : gpmp::ml::SVC
• percentile() : gpmp::stats::Describe
• perform_cross_validation() : gpmp::ml::Kfold
• permutation() : gpmp::Comb
• permutation_p_value() : gpmp::stats::Resampling
• permutation_test() : gpmp::stats::Resampling
• permutations() : gpmp::Comb
• phi() : gpmp::Comb
• Pivot() : gpmp::stats::ProbDist
• PivotFunctionForConfidenceInterval() : gpmp::stats::ProbDist
• planar_gen() : gpmp::Graph
• poisson() : gpmp::stats::CDF , gpmp::stats::PDF
• pollard_rho() : gpmp::Factorization , pygpmp.nt.nt.Factorization
• pollard_rho_log() : gpmp::Logarithms , pygpmp.nt.nt.Logarithms
• power_iter() : gpmp::linalg::Eigen
• power_rule() : gpmp::Differential , pygpmp.calculus.calculus.Differential
• powerMean() : gpmp::ml::Stats
• ppmc() : gpmp::stats::Describe
• predict() : BNN , gpmp::ml::BayesBernoulli , gpmp::ml::BayesClf , gpmp::ml::BayesGauss , gpmp::ml::BayesMultiNom , gpmp::ml::KNN , gpmp::ml::LinearRegression , gpmp::ml::LogReg , gpmp::ml::SVC , pygpmp.ml.ml.LinearRegression
• predict_proba() : gpmp::ml::SVC
• PredictionInterval() : gpmp::stats::ProbDist
• prelu() : gpmp::ml::Activation
• prelu_derivative() : gpmp::ml::Activation
• PRGA() : gpmp::RC4 , pygpmp.nt.nt.RC4
• PrimaryMLP() : gpmp::ml::PrimaryMLP
• print_mtx() : gpmp::linalg::Matrix< Type >
• print_shape() : gpmp::linalg::Matrix< Type >
• printData() : gpmp::core::DataTable
• prior_log_likelihood() : BNN
• prior_variance : BNN
• product_rule() : gpmp::Differential , pygpmp.calculus.calculus.Differential
• prop_backwards() : gpmp::ml::SecondaryMLP< T >
• prop_forwards() : gpmp::ml::SecondaryMLP< T >
• prop_signal() : gpmp::ml::PrimaryMLP
• proportion_z_test() : gpmp::stats::HypothesisTest