Package index • ramp.falciparum

Infection Dynamics Dynamics of MoI, AoI, and the AoY
`zda()`	Compute infection density in a cohort of humans, \(z_\tau(\alpha, a \|h)\)
`truePR()`	Compute the true PR in a cohort as a function of age and exposure
Multiplicity of Infection (MoI) Methods to compute the MoI
`meanMoI()`	The mean MoI in a host cohort of age \(a\)
`dMoIda()`	Derivatives for the queuing model \(M/M/\infty\)
`solveMMinfty()`	Solve the queuing model \(M/M/\infty\)
`MoIDistPlot()`	Plot the output of solveMMinfty
Age of Infection (AoI) Methods to compute the AoI density and distribution functions, random numbers, and moments
`dAoI()`	Compute the density function for AoI
`pAoI()`	Compute the distribution function for AoI
`rAoI()`	Random numbers for the AoI
`momentAoI()`	Compute the moments for the AoI density function for a cohort of age a
Age of the Youngest Infection (AoY) Methods to compute the AoY density and distribution functions, random numbers, and moments
`dAoY()`	The density function for the age of the youngest infection (AoY)
`pAoY()`	The distribution function for the age of the youngest infection (AoY)
`pAoY_long()`	Alternative method for computing the distribution function for the age of the youngest infection (AoY)
`rAoY()`	The random generation function for the age of the youngest infection (AoY)
`momentAoY()`	Compute the moments for the AoY density function for a cohort of age a
Youngest of N Infections (YoN) Methods to compute the YoN density and distribution functions & random numbers
`dYoN()`	The youngest of N infections, density function
`pYoN()`	The youngest of N infections, distribution function
`rYoN()`	The youngest of N infections, random numbers
Hybrid Models Methods to solve hybrid models
`dmda()`	Compute the derivatives for MoI using a hybrid model
`solve_dm()`	Solve the hybrid model for the MoI
`dpda()`	Compute the derivatives for MoI and true PR
`solve_dpda()`	Solve a system of differential equations to compute the true PR and the MoI
`dAoIda()`	Compute the derivatives of the AoI moments dynamically
`solve_dAoI()`	Solve the system of differential equations to compute the moments of the AoI over time.
`dAoYda()`	Compute the derivatives of the approximate moments of the AoY dynamically
`solve_dAoYda()`	Solve the system of differential equations to compute the approximate moments of the AoY over time.
Parasite Densities Expected densities by AoI
F_mu(alpha) A function to compute expected log10 parasites (mu) from the AoI (alpha)
`Fmu()`	Compute mean, expected parasite densities `mu` as a function of the age of infection `alpha`
`sFmu()`	Compute mean, expected parasite densities `mu` for multiple values of the age of infection `alpha`
`Fmu(<W>)`	Compute expected log10 parasite densities, `mu`, as a function of the age of infection `alpha`
`par_Fmu_W()`	Set up parameters for Fmu.W
`Fmu(<base>)`	Compute expected log10 parasite densities, `mu`, as a function of the age of infection `alpha`
`par_Fmu_base()`	Set up parameters for Fmu.base
`Fmu(<chronic>)`	Compute expected log10 parasite densities, `mu`, as a function of the age of infection `alpha`
`par_Fmu_chronic()`	Set up parameters for Fmu.chronic
Omega defined log10 parasites distributions from mu
`d_Omega()`	The density function for parasite densities in a simple malaria infection
`p_Omega()`	The density function for parasite densities as a function of the mean
`q_Omega()`	The quantile function for parasite densities in a simple malaria infection
`r_Omega()`	Random generation of parasite densities from a simple malaria infection
Omega.beta A modified beta distribution for log10 parasite distributions
`par_Omega_beta()`	The quantile function for parasite densities in a simple malaria infection
`d_Omega(<beta>)`	Modified beta distribution, density function
`dbeta1()`	Density function for the beta distribution, an alternative parameterization
`p_Omega(<beta>)`	Modified beta distribution, distribution function
`pbeta1()`	Disribution function for the beta distribution, an alternative parameterization
`q_Omega(<beta>)`	Modified beta distribution, distribution function
`qbeta1()`	The quantile function for the beta distribution, an alternative parameterization
`r_Omega(<beta>)`	Modified beta distribution, random numbers
`rbeta1()`	The random generation function for the beta distribution, an alternative parameterization Title
`sigma_mu()`	A function to compute the variance of the beta distrution as a function of the mean.
`sigma_mu(<abc>)`	A function that returns constrained values of the variance for the beta distrution as a function of the mean.
`par_sigma_abc()`	Parameters to configure sigma_mu.abc
Compute Omega(Fmu(alpha)) log10 parasites from AoI (alpha)
`d_alpha2density()`	The density function for parasite densities in a simple malaria infection of age alpha
`p_alpha2density()`	The distribution function for parasite densities in a simple malaria infection of age alpha
`q_alpha2density()`	The quantile function for parasite densities in a simple malaria infection of age alpha
`r_alpha2density()`	The distribution function for parasite densities in a simple malaria infection of age alpha
Clone Density Parasite density distributions by host cohort age
`d_clone_density()`	Compute \(P_\tau(a \|h)\)
`moments_clone_density()`	Compute the moments of P_density
Parasite Density Compute parasite density distributions as a function of the AoI
`parasite_density()`	Compute \(B_\tau(a \| h)\)
`d_parasite_density()`	Compute the distribution function for \(B_\tau(a)\)
`p_parasite_density()`	Call parasite_density and return the density vector
`r_parasite_density()`	Random generation for parasite densities in a host cohort
`moments_parasite_density()`	Compute the moments of P_density
`rRda()`	Random generation for M parasite densities in a host cohort with MoI
Convolutions Other
`dDensityPaConvolve2()`	The density function for the sum of two infections
`cdfConvolve2()`	The density function for the sum of two infections
`cdfConvolve2a()`	The density function for the sum of two infections, method b
`cdfConvolve2b()`	The density function for the sum of two infections, method a
Sampling
Basic sampling functions Parasite positivity and counts given log10 parasites
`d_detect()`	The probability of detecting parasites
`d_counts()`	The PDF for counting \(x\) parasites
`p_counts()`	The CDF for counting \(x\) parasites
`d_nz_counts_log()`	The PDF for non-zero counts, \(\log_{10}\) transformed
`p_nz_counts_log()`	The CDF for non-zero counts, \(\log_{10}\) transformed
`d_nz_counts_log_binned()`	The binned PDF for non-zero counts, \(\log_{10}\) transformed
`p_nz_counts_log_binned()`	The binned PDF for non-zero counts, \(\log_{10}\) transformed
Poisson Sampling
`par_pois()`	Parameters for Poisson sampling
`d_detect(<pois>)`	Detection of infection given parasitemia
`p_counts(<pois>)`	Detection of infection given parasitemia
`d_counts(<pois>)`	Detection of infection given parasitemia
Negative Binomial Sampling
`par_nb()`	Parameters for negative binomial sampling
`d_detect(<nb>)`	Detection of infection given parasitemia
`p_counts(<nb>)`	Detection of infection given parasitemia
`d_counts(<nb>)`	Negative binomial PDF for raw parasite counts
Parasite Detection and Counts
Observed Prevalence Detection and observed prevalence
`d_detect_mesh()`	Detection of infection given parasitemia
`d_clone_detect()`	Detection of infection given parasitemia
`d_parasite_detect_moi()`	Detection of infection given parasitemia
`d_parasite_detect()`	Detection of infection given parasitemia
`FQ()`	The proportion of zero counts in
Observed MoI Number of Clones Counted
`d_moi_count()`	Detection of infection given parasitemia
Parasite Counts Parasite counts
`d_clone_counts()`	Compute the density of parasite counts for simple infections
`p_clone_counts()`	Compute the distribution of parasite counts for simple infections
`mean_clone_counts()`	Compute the mean parasite counts in simple infections
`d_parasite_counts()`	Compute the density of parasite counts in complex infections
`p_parasite_counts()`	Compute the distribution of parasite counts in complex infections
`mean_parasite_counts()`	Compute the mean parasite counts in complex infections
Force of Infection Methods to set up FoI trace functions
`FoI()`	Force of Infection, \(h_\tau(a)\)
FoI by Age Specialized methods modify the FoI by Age
`ageFoI()`	Functions to modify the FoI by age
`ageFoI(<flat>)`	A function that does not modify the FoI by age
`par_flatAge()`	Make a parameter list to dispatch ageFoI.flat
`ageFoI(<type2>)`	A function that does not modify the FoI by age
`par_type2Age()`	Make a parameter list to dispatch ageFoI.type2
FoI by Season Specialized methods set the seasonal FoI
`seasonalFoI()`	Add a seasonal pattern to the FoI trace function
`seasonalFoI(<exp>)`	A generalized sinusoidal seasonal pattern, exponentiated
`par_expSeason()`	Return a list to dispatch seasonalFoI.exp
`seasonalFoI(<flat>)`	The "no seasonality" function
`par_flatSeason()`	Return a list that dispatches seasonalFoI.flat
`seasonalFoI(<sin>)`	A generalized sinusoidal seasonal pattern
`par_sinSeason()`	Return a list to configure and dispatch seasonalFoI.sin
FoI Trends Specialized methods to set trends in the FoI
`trendFoI()`	Add a trend to the FoI trace function
`trendFoI(<flat>)`	The "no trend" function
`par_flatTrend()`	Return a list that dispatches trendFoI.flat
Utilities Other
`nzPois()`	Compute N non-zero values from a Poisson distribution with a given MoI
Immune Tracking Variables Expected densities by AoI
`Wda()`	Compute immune tracking variables as a function of host age and exposure
`Wda(<none>)`	Compute immune tracking variables as a function of host age and exposure
`par_Wda_none()`	Make a parameter set for Wda.none
`Wda(<delta>)`	Compute immune tracking variables as a function of host age and exposure
`par_Wda_delta()`	Make a parameter set for Wda.none
Red Blood Cells Other
`log10RBC()`	Compute log10 of the red blood cell population
`log10RBC(<static>)`	Compute log10 of the red blood cell population
`par_lRBC_static()`	Set up parameters for log10RBC.static

Reference

Infection Dynamics

Multiplicity of Infection (MoI)

Age of Infection (AoI)

Age of the Youngest Infection (AoY)

Youngest of N Infections (YoN)

Hybrid Models

Parasite Densities

F_mu(alpha)

Omega defined

Omega.beta

Compute Omega(Fmu(alpha))

Clone Density

Parasite Density

Convolutions

Sampling

Basic sampling functions

Poisson Sampling

Negative Binomial Sampling

Parasite Detection and Counts

Observed Prevalence

Observed MoI

Parasite Counts

Force of Infection

FoI by Age

FoI by Season

FoI Trends

Utilities

Immune Tracking Variables

Red Blood Cells