Package {TRSbook}

Weight at Birth

Description

This study focused on risks associated with low weight at birth; the data were collected at the Baystate Medical Centre, Massachusetts, in 1986. Physicians have been interested in low weight at birth for several years, because underweight babies have high rates of infant mortality and infant anomalies. The behaviour of the mother-to-be during pregnancy (diet, smoking habits) can have a significant impact on the chances of having a full-term pregnancy, and thus of giving birth to a child of normal weight. The data file includes information on 189 women (identification number: ID) who came to the centre for consultation. Weight at birth is categorized as low if the child weighs less than 2,500 g.

Usage

data(BIRTH.WEIGHT)

Format

A data frame with 189 observations measured on the following 11 variables.

ID

Numeric. Identification.

AGE

Numeric. Age of mother.

LWT

Numeric. Weight of mother at last menstrual period.

RACE

1=white, 2=black, 3=other. Race of mother.

SMOKE

Yes=1, No=0. Smoking during pregnancy.

PTL

0=none, 1=one, 2=two, etc. Number of premature births in medical history.

HT

Yes=1, No=0. Medical history of hypertension.

UI

Yes=1, No=0. Uterine irritability.

FVT

0=none, 1=one, etc. Number of medical consultations during first trimester

BWT

Numeric. Grams.

LOW

Yes=1, No=0. Weight at birth less than 2,500g

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

Source

https://www.biostatisticien.eu/springeR/

Examples

data(BIRTH.WEIGHT)
str(BIRTH.WEIGHT) 

Body Mass Index of children

Description

This data set comes from an epidemiologic study analyzed by a team from the Institut de sante publique d'epidemiologie et de developpement (ISPED) de Bordeaux. A sample of 152 children (3 or 4 years old) in their first year of kindergarten in schools in Bordeaux (Gironde, SouthWest France) underwent a physical check-up in 1996-1997.

Usage

data(BMI.CHILD)

Format

A data frame with 152 observations measured on the 6 following variables:

GENDER

a factor with levels F and M

zep

a factor with levels Y and N

weight

numeric

years

numeric

months

numeric

height

numeric

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

Source

https://www.biostatisticien.eu/springeR/

Examples

data(BMI.CHILD)
str(BMI.CHILD) 

Study Case of Myocardial Infarction

Description

The study for which the following data were collected aimed at examining whether women who use or have used oral contraceptives are at a higher risk of myocardial infarction. The sample includes 149 women who had myocardial infarction (cases) and 300 women who did not (controls). The main exposure factor is usage of oral contraceptives; the data also include age, weight, height, tobacco consumption, hypertension and family history of cardiovascular diseases.

Usage

data(INFARCTION)

Format

A data frame with 449 observations measured on the following 10 variables:

NUMBER

Identification.

infarct

0 = controls; 1 = cases. Myocardial infarction.

co

0 = never; 1 = yes. Usage of oral contraceptives.

tobacco

0 = no; 1 = smoker; 2 = fromer smoker. Tobacco usage.

age

Age in years.

weight

Weight in kg.

height

Height in cm.

atcd

0 = no; 1 = yes. Family history of cardiovascular diseases.

hta

0 = no; 1 = yes. Hypertension.

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

Source

https://www.biostatisticien.eu/springeR/

Examples

data(INFARCTION)
str(INFARCTION) 

Intima-Media Thickness

Description

Atherosclerosis is the main cause of death for men above 35 and women above 45 in most developed countries. It is a thickening and hardening of internal artery walls. One of its consequences is myocardial infarction. An artery wall is made of three layers; innermost to outermost, they are called intima, media and adventitia. Intima-media thickness is a marker of atherosclerosis. It was measured by ultra- sonography on a sample of 110 subjects in 1999 in Bordeaux hospitals. Information on the main risk factors was also collected.

Usage

data(INTIMA.MEDIA)

Format

A data frame with 110 observations measured on the 9 following variables:

GENDER

1=male, 2=female. Gender.

AGE

Age (in years) at date of consultation.

height

Hieght in cm.

weight

Weight in kg.

tobacco

0=non smoker, 1=former smoker, 2=smoker. Smoking status.

packyear

Number of packs per year. Estimation of tobacco consumption for smokers and former smokers.

SPORT

0=no, 1=yes. Physicial activity.

measure

Intima-media thickness in cm

alcohol

0=non-drinker, 1=occasional drinker, 2=regular drinker. Alcohol consumption.

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

Source

https://www.biostatisticien.eu/springeR/

Examples

data(INTIMA.MEDIA)
str(INTIMA.MEDIA) 

Diet of Elderly People

Description

A sample of 226 elderly people living in Bordeaux (Gironde, South-West France) were interviewed in 2000 for a nutritional study.

Usage

data(NUTRIELDERLY)

Format

A data frame with 226 observations measured on the 13 following variables:

gender

2 = female; 1 = male

situation

1 = single; 2 = living with spouse; 3 = living with family; 4 = living with someone else; Family status.

tea

Number of cups. Daily consumption of tea.

coffee

Number of cups. Daily consumption of coffee

height

Height in cm.

weight

Weight in cm.

age

Age in years at date of interview.

meat

0 = never; 1 = less than once a week; 2 = Once a week; 3 = 2/3 times a week; 4 = 4/6 times a week; 5 = every day. Consumption of meat.

fish

Idem. Consumption of fish.

raw_fruits

Idem. Consumption of raw fruits.

cooked_fruits_veg

Idem. Consumption of cooked fruits and vegetables.

chocol

Idem. Consumption of chocolate.

fat

1 = butter; 2 = margarine; 3 = peanut oil; 4 = sunflower oil; 5 = olive oil; 6 = mix of vegetable oils (e.g., Isio4); 7 = colza oil; 8 = duck or goose fat. Type of fat used for cooking.

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

Source

https://www.biostatisticien.eu/springeR/

Examples

data(NUTRIELDERLY)
str(NUTRIELDERLY) 

Package illustrating the book: The R Software

Description

This package enables one to use some functions used in the book:The R Software, Fundamentals of Programming and Statistical Analysis, Springer, 2014. One can also find the datasets used in the book.

Details

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Book: The R Software, Fundamentals of Programming and Statistical Analysis, Springer, 2014

Address of vector

Description

Object representing an address of numeric vector

Usage

VectorAddr(x)

Arguments

Value

An object of class VectorAddr.

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 9 (Managing Sessions) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

x <- c(8L,9L)
addr <- VectorAddr(x)		# Gets the address of the first
                            # box of the 64-box block where x
                            # is stored.
addr
update(addr,6L) # Write the integer 6 at this address.
x
update(addr+4L,7L) # An integer is coded over 4 bytes,
                      # hence increment the address by 4 to
                      # get to x[2].
x
x <- c(12.8,4.5)
x
addr <- VectorAddr(x)		# Get the address of the first box
                            # of the 128-box block where x is
                            # stored.
update(addr,6.2)
x
update(addr+8L,7.1) # A double is coded over 8 bytes.
x

Adding arrows on statistical plots.

Description

This function add an arrow on the extremities of the axes of a plot

Usage

arrowaxis(x = TRUE, y = TRUE)

Arguments

Value

No return value, called for side effects. The function adds an axis with arrows to the current plot.

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 11 (Descriptive Statistics) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

curve(cos(x),xlim=c(-10,10))
arrowaxis()

Bar charts

Description

Pretty bar charts

Usage

barchart(x, col, my.title, pareto = FALSE, freq.cumul = FALSE, family = "Courier")

Arguments

Value

A plot

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 11 (Descriptive Statistics) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

See Also

barplot

Examples

data(NUTRIELDERLY)
attach(NUTRIELDERLY)
fat <- as.factor(fat)
col <- c("yellow","yellow2","sandybrown","orange",
   "darkolivegreen","green","olivedrab2","green4")
barchart(fat,col,pareto=TRUE)
detach(NUTRIELDERLY)

Decimal representation of a binary number

Description

To compute the decimal representation of a number written in a binary format

Usage

bin2dec(x)

Arguments

Value

Decimal representation of the number x

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 5 (Data Manipulation, Functions) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

bin2dec(1010.101)

Pie chart

Description

A variant of the pie function

Usage

camembert(x, col = NULL, family="Courier")

Arguments

Value

A pie chart

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 11 (Descriptive Statistics) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

See Also

pie

Examples

data(NUTRIELDERLY)
attach(NUTRIELDERLY)
require("RColorBrewer")
col <- brewer.pal(8,"Pastel2")
camembert(fat,col)
detach(NUTRIELDERLY)

Test of the correlation coefficient

Description

Test of the correlation coefficient between two quantitative variables

Usage

cor0.test(x, y, rho0 = 0, alternative = c("two.sided", "less", "greater"))

Arguments

Value

Returns a list:

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 13 (Confidence Intervals and Hypothesis Testing) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

See Also

cor.test

Examples

data(BMI.CHILD)
attach(BMI.CHILD)
cor0.test(weight,height)
detach(BMI.CHILD)

A cross chart

Description

A cross chart displays for each observation a smal cross above the associated modality

Usage

crosschart(x, my.title, col,family="Courier")

Arguments

Value

A cross chart

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 11 (Descriptive Statistics) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

data(NUTRIELDERLY)
attach(NUTRIELDERLY)
situation <- as.factor(situation)
levels(situation) <- c("single","couple","family","other")
crosschart(situation,col=c("orange","darkgreen","black","tan"))
detach(NUTRIELDERLY)

Binary representation of a decimal number

Description

To compute the binary representation of a number written in a decimal format

Usage

dec2bin(x,prec=52)

Arguments

Value

Binary representation of the number x

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 5 (Data Manipulation, Functions) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

dec2bin(10.625,3)

A flashy scatter plot

Description

This function tries to make a nicer plot than the one given by the plot() function for two quantitative variables

Usage

flashy.plot(x,y,my.factor, family = "Courier",xlab="",ylab="")

Arguments

Value

A flashy scatter plot

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 11 (Descriptive Statistics) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

See Also

plot

Examples

data(NUTRIELDERLY)
attach(NUTRIELDERLY)
gender <- as.factor(gender)
levels(gender) <- c("Male","Female")
flashy.plot(weight,height,gender,xlab="Height",ylab="Weight")
detach(NUTRIELDERLY)

Retrieve the address in memory of a variable

Description

Retrieve the address in memory of a numeric variable

Usage

getaddr(x)

Arguments

Value

Integer value of the address of x

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 9 (Managing Sessions) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

x <- c(8L,9L)
addr <- getaddr(x) # Gets the address of the first
                            # box of the 64-box block where x
                            # is stored.
addr
writeaddr(addr,6L) # Write the integer 6 at this address.
x
writeaddr(addr+4L,7L) # An integer is coded over 4 bytes,
                      # hence increment the address by 4 to
                      # get to x[2].
x
x <- c(12.8,4.5)
x
addr <- getaddr(x) # Get the address of the first box
                            # of the 128-box block where x is
                            # stored.
writeaddr(addr,6.2)
x
writeaddr(addr+8L,7.1) # A double is coded over 8 bytes.
x

Moore Penrose inverse

Description

Computes the Moore Penrose inverse of a matrix

Usage

mpinv(M,eps=1e-13)

Arguments

Value

The Moore-Penrose inverse of M

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 10 (Basic Mathematics: Matrix Operations, Integration, and Optimization) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

A <- matrix(c(2,3,5,4),nrow=2,ncol=2)
solve(A)
mpinv(A)
B <- matrix(c(4,2,8,4),nrow=2,ncol=2)
# solve(B) # gives an error.
mpinv(B)

Test of a variance

Description

Comparing the theoretical variance with a reference value

Usage

sigma2.test(x, alternative = "two.sided", var0 = 1, conf.level = 0.95)

Arguments

Value

Returns a list:

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 13 (Confidence Intervals and Hypothesis Testing) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

data(NUTRIELDERLY)
sigma2.test(NUTRIELDERLY$weight,conf.level=0.9)$conf

Comparing statistically two correlation coefficients

Description

Test of the equality of two correlation coefficients

Usage

twosample.cor.test(x1, y1, x2, y2, alpha = 0.05,alternative =
c("two.sided", "less", "greater"))

Arguments

Value

Returns a list:

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 13 (Confidence Intervals and Hypothesis Testing) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

See Also

cor0.test

Examples

data(BMI.CHILD)
attach(BMI.CHILD)
indf <- which(GENDER=="F")  # To  retrieve indices of the females.
indm <- which(GENDER=="M")  # To retrieve indices of the males.
twosample.cor.test(height[indf],weight[indf],
                   height[indm],weight[indm])
detach(BMI.CHILD)

Writing a value at some memory address

Description

Writing a value at some memory address

Usage

writeaddr(addr,newval)

Arguments

Value

Nothing is returned.

Author(s)

Lafaye de Micheaux Pierre <lafaye@unsw.edu.au>, Remy Drouilhet <Remy.Drouilhet@upmf-grenoble.fr>, Liquet Benoit <b.liquet@uq.edu.au>

References

Chapter 9 (Managing Sessions) from the book: The R Software, Fundamentals of Programming and Statistical Analysis

Examples

x <- c(8L,9L)
addr <- getaddr(x) # Gets the address of the first
                            # box of the 64-box block where x
                            # is stored.
addr
writeaddr(addr,6L) # Write the integer 6 at this address.
x
writeaddr(addr+4L,7L) # An integer is coded over 4 bytes,
                      # hence increment the address by 4 to
                      # get to x[2].
x
x <- c(12.8,4.5)
x
addr <- getaddr(x) # Get the address of the first box
                            # of the 128-box block where x is
                            # stored.
writeaddr(addr,6.2)
x
writeaddr(addr+8L,7.1) # A double is coded over 8 bytes.
x