Package {dryingkineticmodels}

dryingkineticmodels: Drying Kinetic Models Comparison and Analysis

Description

Fits multiple thin-layer drying kinetic models to experimental moisture ratio data, compares model performance using statistical criteria, performs residual diagnostics, identifies the best-fitting model, and exports results to Word documents. Twenty models from Ertekin and Firat (2017) doi:10.1016/j.jfoodeng.2016.09.030 are fitted using the Levenberg-Marquardt algorithm described in Marquardt (1963) doi:10.1137/0111030.

Author(s)

Maintainer: Joshy C G cgjoshy@gmail.com

Authors:

• Devika S devikas2104@gmail.com

ANOVA Table for the Best NLS Model

Description

Computes and prints a regression ANOVA table for a fitted nonlinear least squares model.

Usage

anova_nls(best_model, dat)

Arguments

Value

A data frame containing the ANOVA table with columns Source, Sum of Squares, df, Mean Square, F Value, and Pr(>F). The table is also printed to the console.

Compare Fitted Drying Kinetic Models

Description

Computes goodness-of-fit statistics for all successfully fitted models and returns a ranked comparison table.

Usage

compare_models(results)

Arguments

Value

A data frame with one row per successfully fitted model (models with R^2 \le 0 are excluded), sorted by a composite rank score based on R^2, RMSE, and \chi^2. Columns are:

Kinetic Drying Models

Model name.

Functional Form

Equation of the model.

R2

Coefficient of determination.

RMSE

Root mean square error.

MAE

Mean absolute error.

chi2

Reduced chi-squared statistic.

RSS

Residual sum of squares.

Estimated Coefficients

Parameter estimates as a character string.

Interpret Residual Diagnostic Tests

Description

Runs four residual diagnostic tests on the best model and prints a plain-language interpretation of each result.

Usage

diagnostic_interpretation(best_model, verbose = FALSE)

Arguments

Value

A list (returned invisibly) with elements shapiro, dw, bp, and runs — the raw test objects from shapiro.test, dwtest, bptest, and runs.test respectively.

Drying Kinetic Model Comparison and Analysis

Description

Fits 20 thin-layer drying kinetic models to experimental moisture ratio data, ranks them by a composite goodness-of-fit criterion (R^2, RMSE, and \chi^2), identifies the best model, predicts moisture ratio (MR) using the best model, performs residual diagnostic tests, and exports a fully formatted report to a Word document.

Usage

dryingkineticmodels(
  file_path,
  verbose = FALSE,
  models = NULL,
  export_word = FALSE
)

Arguments

Details

The function expects the input to have at least two numeric columns. The first numeric column is treated as drying time as 'time' and the second as moisture ratio as 'MR'. Reorder your columns in Excel if needed before calling the function.

The 20 models fitted are: Lewis, Page, Modified Page, Henderson & Pabis, Logarithmic, Two-Term, Two-Term Exponential, Diffusion Approximation, Wang & Singh, Midilli-Kucuk, Modified Henderson & Pabis, Verma, Weibull, Aghbashlo et al., Jena & Das, Hii et al., Parabolic, Thompson, Demir et al., and Thin-Layer Exponential-Linear. The corresponding names to use with the models argument are "Lewis", "Page", "Modified_Page", "Henderson_Pabis", "Logarithmic", "Two_Term", "Two_Term_Exponential", "Diffusion_Approximation", "Wang_Singh", "Midilli_Kucuk", "Modified_Henderson_Pabis", "Verma", "Weibull", "Aghbashlo", "Jena_Das", "Hii_et_al", "Parabolic", "Thompson", "Demir_et_al", and "Thin_Layer_ExpLin".

Starting values are obtained via a coarse grid search using nlsLM, making the fitting robust across a wide range of datasets without requiring manual starting value specification.

Goodness-of-fit statistics reported are R^2, RMSE, MAE, \chi^2, and RSS. Model ranking uses the combined rank of R^2, RMSE, and \chi^2 following Goyal et al. (2007).

Residual diagnostics include the Shapiro-Wilk test (normality), Durbin-Watson test (autocorrelation), Breusch-Pagan test (homoscedasticity), and Runs test (randomness).

Value

A list (returned invisibly) with five elements:

comparison_table

Data frame of all model fit statistics, sorted by composite rank.

best_model

The result list for the best-fitting model.

anova_table

ANOVA table for the best model.

predicted_MR

Data frame containing observed time, observed MR, predicted MR, residuals, and 95\ the best-fitting model.

columns_used

Data frame recording which input columns were used as TIME and MR. Always check this to confirm correct column selection, especially when verbose = FALSE.

References

Goyal, R. K., Kingsly, A. R. P., Manikantan, M. R., & Ilyas, S. M. (2007). Mathematical modelling of thin layer drying kinetics of plum in a tunnel dryer. Journal of Food Engineering, 79(1), 176–180. doi:10.1016/j.jfoodeng.2006.01.041

Examples

# Small, fast toy example (runs automatically during R CMD check)
toy_df <- data.frame(
  time = c(0, 30, 60, 90, 120, 150),
  MR   = c(1.00, 0.72, 0.51, 0.36, 0.26, 0.18)
)
toy_result <- dryingkineticmodels(toy_df, models = c("Lewis", "Page"),
                                   export_word = FALSE)
toy_result$comparison_table


# Fuller example using a bundled sample dataset (slower, includes Word export)
sample_file <- system.file("extdata", "sample_drying_data.csv",
                           package = "dryingkineticmodels")
df <- read.csv(sample_file)
result <- dryingkineticmodels(df, export_word = TRUE)

Fit All Twenty Drying Kinetic Models

Description

Calls all individual model-fitting functions and returns results as a named list.

Usage

fit_all_models(dat, models = NULL)

Arguments

Value

A named list. Each element is the list returned by the corresponding fit_*() function. Length 20 if models is NULL, otherwise length(models).

Extract and Summarise the Best Model

Description

Identifies the top-ranked model from the comparison table, prints its coefficients, fit statistics, hypothesis test results, and runs residual diagnostics.

Usage

get_best_model(results, comparison, dat, verbose = FALSE)

Arguments

Value

The model result list for the best model (the success = TRUE list returned by the corresponding fit_*() function).

Two-Stage Grid Search for NLS Fitting

Description

Performs a coarse grid search over a parameter grid and returns the best-fitting nonlinear least squares model using nlsLM.

Usage

grid_search_fit_2stage(
  formula,
  data,
  param_grid,
  control = minpack.lm::nls.lm.control(maxiter = 200)
)

Arguments

Value

The best-fitting nls object, or NULL if all starting value combinations failed to converge.

Plot Residual Diagnostics

Description

Produces a 2x2 panel of residual diagnostic plots: residuals vs fitted values, histogram of residuals, normal Q-Q plot, and a residual sequence plot.

Usage

residual_diagnostics(best_model)

Arguments

Value

Called for its side effect (plots). Returns NULL invisibly.