Computation and Estimation of Reliability of Stress-Strength
Models
Reliability of (normal) stress-strength models and for building two-sided or one-sided confidence intervals according to different approximate procedures.

The package provide functions for computing the
reliability of stress-strength models and for building
two-sided or one-sided confidence intervals according to
different approximate procedures

Creates an Adjacency Matrix from a List of Strings
Takes a list of character strings and forms an adjacency matrix for
the times the specified characters appear together in the strings provided. For
use in social network analysis and data wrangling. Simple package, comprised of
three functions.

R Codes and Datasets for Generalized Linear Mixed Models: Modern
Concepts, Methods and Applications by Walter W. Stroup
c(
person(c("Muhammad", "Yaseen"),  email = "myaseen208@gmail.com", role = c("aut", "cre"))
, person(c("Adeela", "Munawar"),  email = "adeela.uaf@@gmail.com", role = c("aut"))
, person(c("Walter", "W.", "Stroup"),  email = "wstroup@unl.edu", role = "ctb")
, person(c("Kent", "M.", "Eskridge"),  email = "keskridge1@unl.edu ", role = "ctb")
)
R Codes and Datasets for Stroup, W. W. (2012). Generalized Linear Mixed Models: Modern Concepts, Methods and Applications, CRC Press.
aod, broom, car, ggplot2, lme4, lmerTest, lsmeans, MASS,
mutoss, nlme, pbkrtest, phia, stats, survey
Muhammad Yaseen [aut, cre],
Adeela Munawar [aut],
Walter W. Stroup [ctb],
Kent M. Eskridge [ctb]

Spatial Structural Diversity Quantification in Raster Data
c(
person("Leila", "Schuh", email = "l.schuh@posteo.net", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5646-7767")),
person("Reinhard", "Furrer", email = "reinhard.furrer@math.uzh.ch", role = "aut", comment = c(ORCID = "0000-0002-6319-2332")),
person("Kalina", "Cherneva", email = "kachernev@gmail.com", role = c("ctb","ctr")),
person("Patrick", "Schratz", role = "ctr"),
person("University Research Priority Progam Global Change and Biodiversity of the University of Zurich", role = "fnd"))
Spatial structural diversity refers to the spatial arrangement of landscape elements and can reveal itself as landscape features, such as patches and line features. The 'R' package 'StrucDiv' provides methods to quantify spatial structural diversity in continuous remote sensing data, or in other data in gridded field format. The methods are based on second-order texture metrics, considering the spatial arrangement of pixel pairs.
Leila Schuh [aut, cre] (<https://orcid.org/0000-0001-5646-7767>),
Reinhard Furrer [aut] (<https://orcid.org/0000-0002-6319-2332>),
Kalina Cherneva [ctb, ctr],
Patrick Schratz [ctr],
University Research Priority Progam Global Change and Biodiversity of
the University of Zurich [fnd]