| Type: | Package |
| Title: | Environmental Probabilistic Risk Assessment Tools |
| Version: | 1.0.1 |
| Date: | 2024-01-23 |
| Description: | It contains functions for dose calculation for different routes, fitting data to probability distributions, random number generation (Monte Carlo simulation) and calculation of systemic and carcinogenic risks. For more information see the publication: Barrio-Parra et al. (2019) "Human-health probabilistic risk assessment: the role of exposure factors in an urban garden scenario" <doi:10.1016/j.landurbplan.2019.02.005>. |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| Imports: | MASS, kSamples, stats, fitdistrplus, truncdist |
| NeedsCompilation: | no |
| Packaged: | 2024-01-29 07:53:03 UTC; fernando.barrio |
| Repository: | CRAN |
| Date/Publication: | 2024-01-30 19:40:02 UTC |
| RoxygenNote: | 7.3.0 |
| Encoding: | UTF-8 |
| Author: | Fernando Barrio-Parra
 [aut, cre,
cph] |
| Maintainer: | Fernando Barrio-Parra <fernando.barrio@upm.es> |
Environmental Probabilistic Risk Assessment Tools
Description
A collection of functions employed in environmental risk assessment to model exposure to a toxicant and predicting health effects, allowing to characterize variability and uncertainty in risk estimations
Details
A set of tools to perform a deterministic and probabilistic risk assessment.
Author(s)
F.Barrio-Parra
Maintainer: fernando.barrio@upm.es
Examples
#### Performs Deterministic Environmental Risk Assessment #####
# Example of dermal contact with a chemical in swiming water
# Estimate the dermal absorbed dose during swiming in waters with a carcinogenic chemical
# (water concentration of 250 mg/m^3)
DWIR ( CW = 250)
# For a systemic effect:
DWIR ( CW= 250, AT=24*365)
# Specifying all the parameters for the carcinogenic case
I = DWIR ( CW=250, IR=1.5, EF = 300, ED = 24, BW = 85)
# Chemical Slope factor
SFAs = 1.5
# Dermal Absorption Factor
ABSAs = 3e-02
# Gastrointestinal Absorption Factor
GIAs = 1
# Risk Estimation
RISKdermal (AD = I, SF = SFAs, GI = GIAs)
#### Perform a test to assess the fitness of a theorical distribution to empirical data ####
set.seed(123)
a <- rnorm(n=100, mean =1.5, sd = 0.25)
b <- rnorm(n = 15, mean = 300, sd = 15)
fit_dist_test(a)
fit_dist_test(b)
# Graphical representation of data fitting to a distribution
plot_fit_dist(a, "norm")
plot_fit_dist(b, "norm")
#### Perform a Probabilistic Environmental Risk Assessment ####
Fita <- Fit_dist_parameter(a)
Fitb <- Fit_dist_parameter(b)
IRr <-random_number_generator(n = 10000, Fited = Fita,
dist = "norm", a =0.8, b = 2.1)
EFr <-random_number_generator(n = 10000, Fited = Fitb,
dist = "norm", a =250, b = 330)
I = DWIR ( CW=250, IR=IRr, EF = EFr, ED = 24, BW = 85)
# Risk Estimation
Risk <- RISKdermal (AD = I, SF = SFAs, GI = GIAs)
hist (Risk)
quantile (Risk, c (0.05, 0.25, 0.5, 0.75, 0.95))
Dermal conctact with chemicals in soil
Description
Estimates the Absorbed dose [mg/Kg*day] of chemicals through dermal contact with a soil
Usage
AD(CS = 1, SA = 2800, AF = 0.2, ABS = 0.001, EF = 350, ED = 24, BW = 70, AT = 365 * 70)
Arguments
CS |
Chemical concentration in soil [mg/Kg] |
SA |
Skin surface area available for contact [cm^2] |
AF |
Skin adherence factor [mg/cm^2] |
ABS |
Absorption factor (Chemical specific) [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical Absorbed dose [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
References
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
Examples
## Estimated absorbed dose for the estimation of carcinogenic effects using
# the default variables (EPA 2011) for a chemical soil concentration of
# 0.2 mg/Kg
AD( CS=0.2)
# For a systemic effect:
AD( CS=0.2, AT=24*365)
# Specifying all the parameters for the carcinogenic case
AD( CS=0.2, SA=2300, AF=0.25, ABS=0.01, EF=150, ED=10, BW=80)
Dermal conctact with chemicals in soil by bootstrap
Description
Dermal conctact with chemicals in soil by bootstrap
Usage
ADboot(n, CS, SA, AF, ABS, EF, ED, BW, AT)
Arguments
n |
Output vector length |
CS |
Chemical concentrtion in soil [mg/Kg] |
SA |
Skin surface area available for contact [cm^2] |
AF |
Skin adherence factor [mg/cm^2] |
ABS |
Absorption factor (Chemical specific) [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical Absorbed dose [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Carcinogenic effects
c <- rnorm( n= 10, mean = 0.2, sd = 0.05 )
b <- rnorm( n= 100, mean = 20, sd = 5 )
ADboot (n = 1000, SA=2300, AF=0.25, ABS=0.01,CS = c, BW = b, ED = 10, EF = 250)
Inhalation of airborne chemicals
Description
Estimates the Intake rate by inhalation of airborne chemicals (vapor phase) [mg/Kg*day]
Usage
AIR(CA = 1, IR = 20, ET = 24, EF = 350, ED = 24, BW = 70, AT = 365 * 70)
Arguments
CA |
Chemical concentrtion in air [mg/m^3] |
IR |
Inhalation Rate [m^3/hour] |
ET |
Exposure time [hours/day] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Intake rate by inhalation of airborne chemicals (vapor phase) I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
References
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
Examples
## Estimated absorbed dose for the estimation of carcinogenic effects using
# the default variables (EPA 2011) for a chemical air concentration
# of 0.2 mg/m^3
AIR ( CA=0.2)
# For a systemic effect:
AIR ( CA=0.2, AT=24*365)
# Specifying all the parameters for the carcinogenic case
AIR ( CA=0.2, IR=25, ET = 24, EF = 300, ED = 24, BW = 85)
Inhalation of airborne chemicals by bootstrap
Description
Estimates the Intake rate by inhalation of airborne chemicals (vapor phase) [mg/Kg*day]
Usage
AIRboot(n, CA, IR, ET, EF, ED, BW, AT)
Arguments
n |
Output vector length |
CA |
Chemical concentrtion in air [mg/m^3] |
IR |
Inhalation Rate [m^3/hour] |
ET |
Exposure time [hours/day] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Intake rate by inhalation of airborne chemicals (vapor phase) I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Carcinogenic effects
c <- rnorm( n= 10, mean = 0.2, sd = 0.05 )
b <- rnorm( n= 100, mean = 20, sd = 5 )
AIRboot (n = 1000, CA=c, IR=25, ET = 24, EF = 300, ED = 24, BW = b)
Chemical intake by Drinking Water
Description
Estimates the chemical Intake rate by Drinking Water [mg/Kg*day]
Usage
DWIR(CW = 1, IRW = 2, EF = 350, ED = 24, BW = 80, AT = 365 * 70)
Arguments
CW |
Chemical concentrtion in water [mg/L] |
IRW |
Water Ingestion Rate [L/Day] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical intake rate by drinking water I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
References
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
Examples
# Estimate the dermal absorbed dose during swiming in waters with a carcinogenic chemical
# (water concentration of 250 mg/m^3)
DWIR ( CW = 250)
# For a systemic effect:
DWIR ( CW= 250, AT=24*365)
# Specifying all the parameters for the carcinogenic case
DWIR ( CW=250, IR=1.5, EF = 300, ED = 24, BW = 85)
Chemical intake by Drinking Water by bootstrap
Description
Estimates the chemical Intake rate by Drinking Water [mg/Kg*day]
Usage
DWIRboot(n, CW, IRW, EF, BW, ED, AT)
Arguments
n |
Output vector length |
CW |
Chemical concentrtion in water [mg/L] |
IRW |
Water Ingestion Rate [L/Day] |
EF |
Exposure frequency [day/yr] |
BW |
Body weight [Kg] |
ED |
Exposure duration [yr] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical intake rate by drinking water I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Carcinogenic effects
c <- rnorm( n= 10, mean = 250, sd = 15 )
b <- rnorm( n= 100, mean = 20, sd = 5 )
DWIRboot (n = 1000, CW=c, IR=1.5, EF = 300, ED = 24, BW = b)
Returns adjusted distribution parameters
Description
Returns the distribution parameters adjusted for by maximum likelihood (mle) for the following distributions: "normal","log-normal","geometric","exponential","Poisson", "cauchy" , "logistic" and "weibull"
Usage
Fit_dist_parameter(x)
Arguments
x |
A numeric vector of length at least one containing only finite values (non-censored data) |
Value
normal |
Fitted Mean and sd for a normal distribution |
`log-normal` |
Fitted Meanlog and sdlog for a log-normal distribution |
geometric |
Fitted prob for a geometric distribution |
exponential |
Fitted rate for a exponential distribution |
Poisson |
Fitted lambda for a exponential distribution |
cauchy |
Fitted location and scale for a Cauchy distribution |
logistic |
Fitted location and scale for a Logistic distribution |
weibull |
Fitted shape and scale for a weibull distribution |
Author(s)
F. Barrio-Parra
See Also
Function fitdistr in Library (MASS)
Examples
a <- rnorm(n=100, mean =10, sd = 1)
b <- Fit_dist_parameter(a)
# Examples of result extraction
b$normal
b$weibull
Hazard Index
Description
Returns the Hazard Index (non carcinogenic effects)
Usage
HI(I, RFD)
Arguments
I |
Intake Rate [mg/Kg*day] |
RFD |
Reference dose [mg/Kg*day] |
Value
Hazard Index [-] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Assessing if there is systemic risk for an adult receptor that drinks water with 1000 ug/L
# of hexaclorobence (Reference Dose (IRIS data base) = 8e-04 [mg/Kg*day]) in a residencial
# scenario (default EPA Maximum Reasonable Exposure parameters)
HI (I = DWIR( CW=1, AT=24*365), RFD = 8e-04)
Hazard Index for dermal contact
Description
Returns the Hazard Index for dermal exposure with chemicals (non carcinogenic effects)
Usage
HIdermal(AD, RFD, GI)
Arguments
AD |
Absorbed dose [mg/Kg*day] |
RFD |
Reference dose [mg/Kg*day] |
GI |
Gastrointestinal Absorption factor (chemical specific) [-] |
Value
Hazard Index [-] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Assess if there is non-carcinogenic risk for an dadult thorug dermal
# contact exposed to a soil that contains 45 mg/Kg of As in a residencial
# scenario (default EPA Maximum Reasonable Exposure parameters)
RfDAs = 3e-04
# Dermal Absorption Factor
ABSAs = 3e-02
# Gastrointestinal Absorption Factor
GIAs = 1
I = AD (CS = 45,ABS = ABSAs, AT= 24*365)
HIdermal (AD = I, RFD = RfDAs, GI = GIAs)
Hazard Index for inhalation of vapors
Description
Returns the Hazard Index (systemic effects) for inhalation of vapors
Usage
HIinhal(INH, RFC)
Arguments
INH |
Inhalated dose (mg/m^3) |
RFC |
Reference concentration (mg/m^3) |
Value
Hazard Index (non carcinogenic effects) [-] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Assess if there is systemic risk for the exposure of an adult
# (Reasonable Maximum Exposure) to a Toluene air concentration of 2 mg/ m^3
HIinhal (INH = AIR (CA = 2, AT = 365*24), RFC = 5)
Inhalation of resuspended soil particles
Description
Estimates the Intake rate of chemicals by inhalation of resuspended soil particles [mg/Kg*day]
Usage
INH(C = 10, EF = 350, ED = 24, PEF = 1.36^9, AT = 365 * ED)
Arguments
C |
Concentration of chemicals in soil(mg/kg) |
EF |
Exposure frequency (day/year) |
ED |
Exposure duration (years) |
PEF |
Particle emision factor meaning resuspended particles(m^3/kg) |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical intake rate by inhalation of soil particles I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
References
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
Examples
# Estimated dose for the estimation of carcinogenic effects due to the
# inhalation of soil particles that contains 45 mg/Kg of As in a residencial
# scenario (default EPA Maximum Reasonable Exposure parameters)
INH(C= 45, AT = 365*70)
# For non-carcinogenic effects:
INH(C= 45)
Risk
Description
Returns the Risk estimation (carcinogenic effects)
Usage
RISK(I, SF)
Arguments
I |
Intake Rate [mg/Kg*day] |
SF |
Slope Factor [(mg/Kg*day)^-1] (chemical specific) |
Value
Risk [-] - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
# Assessing if there is carcinogenic risk for an adult receptor that drinks water with 1000 ug/L
# of hexaclorobence (Oral Slope Factor (IRIS data base) = 1.6 [mg/Kg*day]^-1) in a residencial
# scenario (default EPA Maximum Reasonable Exposure parameters)
RISK (I = DWIR( CW=1), SF = 1.6)
Risk for inhalation of vapors
Description
Returns the risk (carcinogenic effects) for inhalation of vapors
Usage
RISKInhal(URi, I)
Arguments
URi |
Inhalation Unit risk [(ug/m^3)^-1] |
I |
Inhalated dose (mg/m^3) |
Value
Risk [-] - Object class "numeric"
Examples
# Assess if there is cancer risk for the exposure of an adult
# (Reasonable Maximum Exposure) to a benzene air concentration of 2 mg/ m^3
RISKInhal ( I = AIR (CA = 2), URi = 7.8e-06)Risk for dermal contact
Description
Returns the Risk for dermal exposure with chemicals (carcinogenic effects)
Usage
RISKdermal(AD, SF, GI)
Arguments
AD |
Absorbed dose [mg/Kg*day] |
SF |
Slope Factor [(mg/Kg*day)^-1] (chemical specific) |
GI |
Gastrointestinal Absorption factor (chemical specific) [-] |
Value
Risk [-] - Object class "numeric"
Author(s)
F. Barrio-Parra
See Also
AD
Examples
# Assess if there is carcinogenic risk for an dadult thorug dermal
# contact exposed to a soil that contains 45 mg/Kg of As in a residencial
# scenario (default EPA Maximum Reasonable Exposure parameters)
SFAs = 1.5
# Dermal Absorption Factor
ABSAs = 3e-02
# Gastrointestinal Absorption Factor
GIAs = 1
I = AD (CS = 45,ABS = ABSAs)
RISKdermal (AD = I, SF = SFAs, GI = GIAs)Chemical intake by accidental soil ingestion
Description
Estimates the chemical Intake rate by accidental soil ingestion [mg/Kg*day]
Usage
SIR(CS = 1, IR = 100, FI = 1, EF = 350, ED = 24, BW = 80, AT = 365 * 70)
Arguments
CS |
Chemical concentrtion in soil [mg/Kg] |
IR |
Soil Ingestion Rate [mg/Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical intake rate by soil ingestion I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
References
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
Examples
# Ingestion rate for a children weighing 20 Kg who ingest 200 mg
# of soil every day, 250 days per year during 10 years. 95-UCL of
# Arsenic in soil is 25 mg/Kg
# Carcinogenic effects
SIR ( CS = 25, BW = 20, IR = 200, ED = 10, EF = 250)
# Systemic effects
SIR ( CS = 25, BW = 20, IR = 200, ED = 10, EF = 250, AT = 365*10)
Chemical intake by accidental soil ingestion by bootstrap
Description
Estimates the chemical Intake rate by accidental soil ingestion [mg/Kg*day]
Usage
SIRboot(n, CS, IR, FI, EF, ED, BW, AT)
Arguments
n |
Output vector length |
CS |
Chemical concentrtion in soil [mg/Kg] |
IR |
Soil Ingestion Rate [mg/Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight [Kg] |
AT |
Averaging time [day] (Note that for No carcinogenic effects AT should be equal to 365*ED) |
Value
Chemical intake rate by soil ingestion I [mg/Kg*day] - Object class "numeric"
Examples
# Carcinogenic effects
c <- rnorm( n= 10, mean = 22, sd = 2 )
b <- rnorm( n= 100, mean = 20, sd = 5 )
SIRboot (n = 1000, CS = c, BW = b, IR = 200, ED = 10, EF = 250)
Chemical intake by ingestion of vegetables
Description
Estimates the chemical Intake rate by ingestion of contaminated fruits and vegetables [mg/Kg*day]
Usage
VI(CF = 1, IR = 210, FI = 1, EF = 350, ED = 24, BW = 80, AT = 365 * 70)
Arguments
CF |
Chemical concentration in food [mg/Kg] |
IR |
Vegetables Ingestion Rate [g / Kg * Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body weight (kg) |
AT |
Averaging time [day] (For No carcinogenic effects AT = 365*ED) |
Value
Chemical intake rate by vegetable ingestion I [mg/Kg*day] - Object class "numeric"
Author(s)
F. Barrio-Parra
References
US Environmental Protection Agency, 2011. Exposure Factors Handbook: 2011 Edition. U.S. Environmental Protection Agency, EPA/600/R-(September), pp 1466.
Examples
# Assess the chemical intake by an adult that eats lettuce with a concentration of 2 mg/ Kg
# in a maximum reasonable exposure scenario for non- carcinogenic effects
VI (CF = 2, AT = 365*24)
Chemical intake by ingestion of vegetables by bootstrap
Description
Estimates the chemical Intake rate by ingestion of contaminated fruits and vegetables [mg/Kg*day]
Usage
VIboot( n, CF, IR, FI, EF, ED, BW, AT)
Arguments
n |
Output vector length |
CF |
Chemical concentrtion in food [mg/Kg] |
IR |
Vegetables Ingestion Rate [g / Kg * Day] |
FI |
Fraction ingested from contaminated source [-] |
EF |
Exposure frequency [day/yr] |
ED |
Exposure duration [yr] |
BW |
Body Weight [Kg] |
AT |
Averaging time [day] (For No carcinogenic effects AT = 365*ED) |
Value
A vector of Chemical intake rate by vegetable ingestion I [mg/Kg*day] - Object class "numeric"
Examples
# Assess the chemical intake by an adult that eats lettuce with a concentration of 2 mg/ Kg of a
# chemical with non- carcinogenic effects in a maximum reasonable exposure scenario
# Figure out 10 data of Chemical concentration following a normal distribution (mean = 2, sd= 2)
# and 100 Body weight data that follow a normal distribution (mean = 70, sd = 15)
c <- rnorm( n= 10, mean = 2, sd = 2 )
b <- rnorm( n= 100, mean = 70, sd = 5 )
VIboot (n = 1000, CF = c, BW = b, AT = 365*24)
p-value significance checking function
Description
Auxiliar function to check p-value significance (Function created for internal use of the model).
Usage
condition(n)
Arguments
n |
p-value |
Value
Return "Significant" or "Not-significant" - Object class "character"
Examples
condition ( 0.001)
condition (0.1)
Extracts the fitted distribution parameters to be introduced in other function
Description
Auxiliar function for internal use only
Usage
extr_par(x, dist)
Arguments
x |
List of parameters obtained by the aplication of the Fit_dist_parameter function |
dist |
Name of the distribution we would like to stract the parameters ("norm", "lnorm", "geom", "exp", "pois", "gamma", "cauchy", "logis", "weibull", "nbinom", "beta", "chisq", "t", "f") |
Value
A list of fitted parameters.
Author(s)
F. Barrio-Parra
Examples
a <- rnorm(n=100, mean =10, sd = 1)
b <- Fit_dist_parameter(a)
extr_par(x = b, dist ="norm")
Summary of Godness-of-fit tests
Description
Returns a data frame with the summary of Fiting distribution tests for the following distributions: "normal","log-normal","geometric","exponential","Poisson", "cauchy" , "logistic" and "weibull".
The considered Godness-of-fit tests are: Bayesian Information Criterium (BIC), Akaike Information Criterium (AIC), Kolmogorov-Smirnov test and Anderson-Darling test.
Usage
fit_dist_test(x)
Arguments
x |
A numeric vector of length at least one containing only finite values |
Value
Distribution |
Name of the tested distribution |
BayesianIC |
Bayesian Information Criterium (BIC) |
AkaikeIC |
Akaike Information Criterium (AIC) |
Kol-SmirD |
The value of the Kolmogorov-Smirnov test statistic |
Kol-SmirPvalue |
The value of the Kolmogorov-Smirnov test p-value |
Signigicance KS |
A column to check the significance of the Kolmogorov-Smirnov test |
And-Darl |
The value of the nderson-Darling test statistic |
And-DarlPvalue |
The value of the Anderson-Darling test p-value |
Signigicance AD |
A column to check the significance of the Anderson-Darling test |
Author(s)
F. Barrio-Parra
See Also
ad.test library(kSamples), AIC library(stats), BIC library(stats), ks.test library(stats),
Examples
set.seed(123)
a <- rnorm(n=100, mean =10, sd = 1)
fit_dist_test(a)
b<- rexp(n = 100,rate = 1)
fit_dist_test(b)
Graphical representation of data fitting to a distribution
Description
A function to help assessing the distribution that best fit a data vector
Usage
plot_fit_dist(x, dist)
Arguments
x |
A numeric vector of length at least one containing only finite values (values must be >= 0) |
dist |
Character vector indicating the distribution to be ploted:"norm", "lnorm", "geom", "exp", "pois", "cauchy", "logis", "weibull" |
Value
Returns: Empirical and theoretical density plots, Empirical and theoretical CDFs, Q-Q plot, P-P plot
Author(s)
F. Barrio-Parra
See Also
plotdist from Library (fitdstrplus)
Examples
set.seed(123)
a <- rnorm(n = 100, mean = 10, sd = 1)
plot_fit_dist(a, "norm")
Random number generator
Description
Return a vector of n random numbers following a truncated distribution (dist) in agreement with a fitted parameters "Fited"
Usage
random_number_generator(n, Fited, dist, a, b)
Arguments
n |
The number of desired generated numbers |
Fited |
A list contaning the parameters obtained by application of Fit_dist_parameter |
dist |
Character vector indicating the distribution to be applied:"norm", "lnorm", "geom", "exp", "pois", "cauchy", "logis", "weibull" |
a |
Truncation Lower limit |
b |
Truncation Upper limit |
Value
A vector of n random numbers - Object class "numeric"
Author(s)
F. Barrio-Parra
See Also
Fit_dist_parameter
Examples
set.seed(123)
a <- rnorm(n = 100, mean = 10, sd = 1)
Fit <- Fit_dist_parameter(a)
b <-random_number_generator(n = 10000, Fited = Fit,
dist = "norm", a =8, b = 12)
hist(a,xlim= c(7,14))
hist(b,xlim= c(7,14))
Execute sampling with replacement
Description
Auxiliar function (employed only for internal use)
Usage
sampler(n, a)
Arguments
n |
Number of sampling iterations |
a |
data vector |
Value
Resampled vector of length n - Object class "numeric"
Author(s)
F. Barrio-Parra
Examples
a <- rnorm (n = 20, mean = 0, sd = 1)
b <- sampler (n = 100, a = a)
Significance level cheking function
Description
Function that return if the p-value allows to accept H0 in a Kolmogorov Smirnov or Anderson Darling test
Usage
sig(n)
Arguments
n |
p-value |
Value
Text string ("Significant"" / "Not Significant"") - Object class "character"
Examples
sig ( 0.001 )
sig ( 0.1 )