View source: R/pathway_model.R
| pathway_model | R Documentation | 
Estimates the number of potential founder populations (NPFP) of a pest
in different regions, using N_{trade} data combined with additional user-defined
parameters.
pathway_model(
  ntrade_data,
  IDs_col,
  values_col,
  expression,
  parameters,
  niter = 100
)
| ntrade_data | A data frame with the quantity of potentially infested commodities
imported from third countries where the pest is present ( | 
| IDs_col | A string specifying the column name in  | 
| values_col | A string specifying the column name in  | 
| expression | A string of characters representing the equation for the pathway model.
This expression must not include  
 | 
| parameters | A named list specifying the distributions for each parameter
used in  
 See details on Parameter distributions for a list of available distributions and examples on how to specify them. | 
| niter | The number of iterations to generate random samples from the distributions. The default is 100 iterations. | 
The use of ISO 3166 (alpha-2) codes
(ISO 3166 Maintenance Agency),
or NUTS codes in the case of European countries
Nomenclature of territorial units for statistics,
as country or region identifiers (IDs_col) is recommended
for subsequent compatibility with other functions of the  qPRAentry package.
The following distributions are supported. For details on their parameters, refer to the linked R documentation:
| Distribution |   | Documentation | 
| "beta" |   | rbeta()(Beta distribution) | 
| "binom" |   | rbinom()(Binomial distribution) | 
| "cauchy" |   | rcauchy()(Cauchy distribution) | 
| "chisq" |   | rchisq()(Chi-squared distribution) | 
| "exp" |   | rexp()(Exponential distribution) | 
| "f" |   | rf()(F distribution) | 
| "gamma" |   | rgamma()(Gamma distribution) | 
| "geom" |   | rgeom()(Geometric distribution) | 
| "lnorm" |   | rlnorm()(Log-normal distribution) | 
| "nbinom" |   | rnbinom()(Negative Binomial distribution) | 
| "norm" |   | rnorm()(Normal distribution) | 
| "pois" |   | rpois()(Poisson distribution) | 
| "t" |   | rt()(Student's t distribution) | 
| "unif" |   | runif()(Uniform distribution) | 
| "weibull" |   | rweibull()(Weibull distribution) | 
For example, to specify a normal distribution with mean 0 and standard deviation 1:
list(dist = "norm", mean = 0, sd = 1)
Ensure that all parameters required by the chosen distribution are included.
A data frame with the statistics (mean, SD, minimum, first quartile,
median, third quartile, and maximum) resulting from the iterations of the NPFP
for each country/region and for the total (i.e., the results for the set of all
countries/regions).
ntrade()
## Example using Northern American countries and ntrade simulated data
data("datatrade_NorthAm")
# Extract country IDs and simulate ntrade data
IDs <- datatrade_NorthAm$internal_production$reporter
df <- data.frame(IDs = IDs,
                 ntrade_values = abs(rnorm(length(IDs), 10000, 2000)))
# Expression for the pathway model using 3 parameters
eq <- "(1/P1)*P2*P3"
# Distribution for each parameter
parameters <- list(
  P1 = list(dist = "beta", shape1 = 0.5, shape2 = 1),
  P2 = list(dist = "gamma", shape = 1.5, scale = 100),
  P3 = list(dist = "lnorm", mean = 5, sd = 2)
)
# Run pathway_model()
res_pathway <- pathway_model(ntrade_data = df,
                             IDs_col = "IDs",
                             values_col = "ntrade_values",
                             expression = eq,
                             parameters = parameters,
                             niter = 100)
head(res_pathway)
# summary of the total for all countries
res_pathway[res_pathway$IDs == "Total",]
# plot
plot_countries(res_pathway, "IDs", "Median")
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