A first course in statistical programming with R:
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Book |
| Language: | English |
| Published: |
Cambridge [u.a.]
Cambridge Univ. Press
2007
|
| Edition: | 1. publ. |
| Subjects: | |
| Online Access: | Inhaltsverzeichnis Klappentext |
| Physical Description: | X, 163 S. Illustrationen |
| ISBN: | 9780521694247 9780521872652 |
Staff View
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
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| 003 | DE-604 | ||
| 005 | 20230830 | ||
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| 008 | 071031s2007 a||| |||| 00||| eng d | ||
| 020 | |a 9780521694247 |c pbk |9 978-0-521-69424-7 | ||
| 020 | |a 9780521872652 |c hbk |9 978-0-521-87265-2 | ||
| 035 | |a (OCoLC)254096826 | ||
| 035 | |a (DE-599)BVBBV022945077 | ||
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| 100 | 1 | |a Braun, W. John |d 1963- |e Verfasser |0 (DE-588)13396440X |4 aut | |
| 245 | 1 | 0 | |a A first course in statistical programming with R |c W. John Braun and Duncan J. Murdoch |
| 250 | |a 1. publ. | ||
| 264 | 1 | |a Cambridge [u.a.] |b Cambridge Univ. Press |c 2007 | |
| 300 | |a X, 163 S. |b Illustrationen | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 7 | |a Programmeren (computers) |2 gtt | |
| 650 | 7 | |a R (computerprogramma) |2 gtt | |
| 650 | 4 | |a Datenverarbeitung | |
| 650 | 4 | |a Statistik | |
| 650 | 4 | |a R (Computer program language) | |
| 650 | 4 | |a Statistics |x Data processing | |
| 650 | 0 | 7 | |a Statistik |0 (DE-588)4056995-0 |2 gnd |9 rswk-swf |
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
| 689 | 0 | 0 | |a Statistik |0 (DE-588)4056995-0 |D s |
| 689 | 0 | 1 | |a R |g Programm |0 (DE-588)4705956-4 |D s |
| 689 | 0 | |5 DE-604 | |
| 700 | 1 | |a Murdoch, Duncan J. |d 1959- |e Verfasser |0 (DE-588)1117735443 |4 aut | |
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| 856 | 4 | 2 | |m Digitalisierung UB Regensburg |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016149658&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |3 Klappentext |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-016149658 | ||
Record in the Search Index
| _version_ | 1804137184850083840 |
|---|---|
| adam_text | Contents
I Preface page
ix
I
1
Getting started
ι
1.1
What is statistical programming?
1
1.2
Outline of the book
2
1.3
The
R
package
3
1.4
Why use a command line?
3
1.5
Font conventions
4
1.6
Installation of
R
4
2
I Introduction to the
R
language
2.1
Starting and quitting
R
5
2.1.1
Recording your work
6
2.2
Basic features of
R
7
2.2.1
Calculating with
R
7
2.2.2
Named storage
7
2.2.3
Functions
9
2.2.4
Exact or approximate?
9
2.2.5
R
is case-sensitive
12
2.2.6
Listing the objects in the workspace
12
2.2.7
Vectors
12
2.2.8
Extracting elements from vectors
13
2.2.9
Vector arithmetic
14
2.2.10
Simple patterned vectors
15
2.2.11
Missing values and other special values
16
2.2.12
Character vectors
16
2.2.13
Factors
17
2.2.14
More on extracting elements from vectors
18
2.2.15
Matrices and arrays
18
2.2.16 Dataframes 19
2.2.17
Dates and times
21
2.3
Built-in functions and online help
21
2.3.1
Built-in examples
22
2.3.2
Finding help when you don t know
the function name
23
2.3.3
Built-in graphics functions
23
2.3.4
Additional elementary built-in functions
25
2.4
Logical vectors and relational operators
26
2.4.1
Boolean algebra
26
2.4.2
Logical operations in
R
27
2.4.3
Relational operators
28
2.5
Data input and output
29
2.5.1
Changing directories
29
CONTENTS
2.5.2
dump
( )
and source
( )
29
2.5.3
Redirecting
R
output
30
2.5.4
Saving and retrieving image files
31
2.5.5
Data frames and the read
.
table function
31
2.5.6
Lists
31
Chapter exercises
32
3 !
Programming statistical graphics
33
3.1
High-level plots
33
3.1.1
Bar charts and dot charts
34
3.1.2
Pie charts
35
3.1.3
Histograms
35
3.1.4
Box plots
36
3.1.5
Scatterplots
38
3.1.6
QQ plots
39
3.2
Choosing a high-level graphic
41
3.3
Low-level graphics functions
42
3.3.1
The plotting region and margins
42
3.3.2
Adding to plots
43
3.3.3
Setting graphical parameters
45
Chapter exercises
46
4 1
Programming with
R
47
4.1
Flow control
47
4.1.1
The for() loop
47
4.1.2
The
i f
()
statement
50
4.1.3
The while
()
loop
54
4.1.4
Newton s method for root finding
55
4.1.5
The repeat loop, and the break and next statements
57
4.2
Managing complexity through functions
59
4.2.1
What are functions?
59
4.2.2
Scope of variables
62
4.3
Miscellaneous programming tips
63
4.3.1
Using fix
()
63
4.3.2
Documentation using
#
64
4.4
Some general programming guidelines
65
4.4.1
Top-down design
67
4.5
Debugging and maintenance
72
4.5.1
Recognizing that a bug exists
72
4.5.2
Make the bug reproducible
73
4.5.3
Identify the cause of the bug
73
4.5.4
Fixing errors and testing
75
4.5.5
Look for similar errors elsewhere
75
4.5.6
The browser
()
and debug
()
functions
75
4.6
Efficient programming
77
4.6.1
Learn your tools
77
4.6.2
Use efficient algorithms
78
4.6.3
Measure the time your program takes
79
CONTENTS
4.6.4
Be willing to use different tools
80
4.6.5
Optimize with care
80
Chapter exercises
80
5
Simulation
82
5.1
Monte Carlo simulation
82
5.2
Generation of pseudorandom numbers
83
5.3
Simulation of other random variables
88
5.3.1
Bernoulli random variables
88
5.3.2
Binomial random variables
89
5.3.3
Poisson
random variables
93
5.3.4
Exponential random numbers
97
5.3.5
Normal random variables
99
5.4
Monte Carlo integration
101
5.5
Advanced simulation methods
104
5.5.1
Rejection sampling
104
5.5.2
Importance sampling
107
Chapter exercises
109
6
і
Computational linear algebra
112
6.1
Vectors and matrices in
R
113
6.1.1
Constructing matrix objects
113
6.1.2
Accessing matrix elements; row and column names
115
6.1.3
Matrix properties
117
6.1.4
Triangular matrices
118
6.1.5
Matrix arithmetic
118
6.2
Matrix multiplication and inversion
119
6.2.1
Matrix inversion
120
6.2.2
The
W
decomposition
121
6.2.3
Matrix inversion in
R
122
6.2.4
Solving linear systems
123
6.3
Eigenvalues and eigenvectors
124
6.4
Advanced topics
125
6.4.1
The singular value decomposition of a matrix
125
6.4.2
The Choleski decomposition of a positive definite matrix
126
6.4.3
The QR decomposition of a matrix
127
6.4.4
The condition number of a matrix
128
6.4.5
Outer products
129
6.4.6 Kronecker
products
129
6.4.7
apply
( )
129
Chapter exercises
130
7 1
Numerical optimization
132
7.1
The golden section search method
132
7.2
Newton-Raphson
135
7.3
The Nelder-Mead simplex method
138
7.4
Built-in functions
142
viii
1 CONTENTS
7.5
Linear programming
142
7.5.1
Solving linear programming problems in
R
145
7.5.2
Maximization and other kinds of constraints
145
7.5.3
Special situations
146
7.5.4
Unrestricted variables
149
7.5.5
Integer programming
150
7.5.6
Alternatives to
lp
( )
151
7.5.7
Quadratic programming
151
Chapter exercises
157
Appendix
Review of random variables
і
and distributions
158
1
index
161
This is the only introduction you ll need to start programming in R, the open-source
language that is free to download and lets you adapt the source code for your own
requirements. Co-written by one of the RCore Development Team, and by an
established
R
author, this book comes with real
R
code that complies with the
standards of the language.
•
Self-contained first course in statistical computing
•
Accessible to any student familiar with university-level calculus
•
The basics of
R
syntax and statistical graphics are explained, and elementary
programming is discussed
•
Programming applications in simulation and optimization as well as numerical
linear algebra are introduced
•
Many worked examples with notes on understanding the code
•
All examples are drawn from statistical applications
•
End-of-chapter review questions plus over
150
exercises; data sets and solutions
all available on web
|
| adam_txt |
Contents
I Preface page
ix
I
1
Getting started
ι
1.1
What is statistical programming?
1
1.2
Outline of the book
2
1.3
The
R
package
3
1.4
Why use a command line?
3
1.5
Font conventions
4
1.6
Installation of
R
4
2
I Introduction to the
R
language
2.1
Starting and quitting
R
5
2.1.1
Recording your work
6
2.2
Basic features of
R
7
2.2.1
Calculating with
R
7
2.2.2
Named storage
7
2.2.3
Functions
9
2.2.4
Exact or approximate?
9
2.2.5
R
is case-sensitive
12
2.2.6
Listing the objects in the workspace
12
2.2.7
Vectors
12
2.2.8
Extracting elements from vectors
13
2.2.9
Vector arithmetic
14
2.2.10
Simple patterned vectors
15
2.2.11
Missing values and other special values
16
2.2.12
Character vectors
16
2.2.13
Factors
17
2.2.14
More on extracting elements from vectors
18
2.2.15
Matrices and arrays
18
2.2.16 Dataframes 19
2.2.17
Dates and times
21
2.3
Built-in functions and online help
21
2.3.1
Built-in examples
22
2.3.2
Finding help when you don't know
the function name
23
2.3.3
Built-in graphics functions
23
2.3.4
Additional elementary built-in functions
25
2.4
Logical vectors and relational operators
26
2.4.1
Boolean algebra
26
2.4.2
Logical operations in
R
27
2.4.3
Relational operators
28
2.5
Data input and output
29
2.5.1
Changing directories
29
CONTENTS
2.5.2
dump
( )
and source
( )
29
2.5.3
Redirecting
R
output
30
2.5.4
Saving and retrieving image files
31
2.5.5
Data frames and the read
.
table function
31
2.5.6
Lists
31
Chapter exercises
32
3 !
Programming statistical graphics
33
3.1
High-level plots
33
3.1.1
Bar charts and dot charts
34
3.1.2
Pie charts
35
3.1.3
Histograms
35
3.1.4
Box plots
36
3.1.5
Scatterplots
38
3.1.6
QQ plots
39
3.2
Choosing a high-level graphic
41
3.3
Low-level graphics functions
42
3.3.1
The plotting region and margins
42
3.3.2
Adding to plots
43
3.3.3
Setting graphical parameters
45
Chapter exercises
46
4 1
Programming with
R
47
4.1
Flow control
47
4.1.1
The for() loop
47
4.1.2
The
i f
()
statement
50
4.1.3
The while
()
loop
54
4.1.4
Newton's method for root finding
55
4.1.5
The repeat loop, and the break and next statements
57
4.2
Managing complexity through functions
59
4.2.1
What are functions?
59
4.2.2
Scope of variables
62
4.3
Miscellaneous programming tips
63
4.3.1
Using fix
()
63
4.3.2
Documentation using
#
64
4.4
Some general programming guidelines
65
4.4.1
Top-down design
67
4.5
Debugging and maintenance
72
4.5.1
Recognizing that a bug exists
72
4.5.2
Make the bug reproducible
73
4.5.3
Identify the cause of the bug
73
4.5.4
Fixing errors and testing
75
4.5.5
Look for similar errors elsewhere
75
4.5.6
The browser
()
and debug
()
functions
75
4.6
Efficient programming
77
4.6.1
Learn your tools
77
4.6.2
Use efficient algorithms
78
4.6.3
Measure the time your program takes
79
CONTENTS
4.6.4
Be willing to use different tools
80
4.6.5
Optimize with care
80
Chapter exercises
80
5
Simulation
82
5.1
Monte Carlo simulation
82
5.2
Generation of pseudorandom numbers
83
5.3
Simulation of other random variables
88
5.3.1
Bernoulli random variables
88
5.3.2
Binomial random variables
89
5.3.3
Poisson
random variables
93
5.3.4
Exponential random numbers
97
5.3.5
Normal random variables
99
5.4
Monte Carlo integration
101
5.5
Advanced simulation methods
104
5.5.1
Rejection sampling
104
5.5.2
Importance sampling
107
Chapter exercises
109
6
і
Computational linear algebra
112
6.1
Vectors and matrices in
R
113
6.1.1
Constructing matrix objects
113
6.1.2
Accessing matrix elements; row and column names
115
6.1.3
Matrix properties
117
6.1.4
Triangular matrices
118
6.1.5
Matrix arithmetic
118
6.2
Matrix multiplication and inversion
119
6.2.1
Matrix inversion
120
6.2.2
The
W
decomposition
121
6.2.3
Matrix inversion in
R
122
6.2.4
Solving linear systems
123
6.3
Eigenvalues and eigenvectors
124
6.4
Advanced topics
125
6.4.1
The singular value decomposition of a matrix
125
6.4.2
The Choleski decomposition of a positive definite matrix
126
6.4.3
The QR decomposition of a matrix
127
6.4.4
The condition number of a matrix
128
6.4.5
Outer products
129
6.4.6 Kronecker
products
129
6.4.7
apply
( )
129
Chapter exercises
130
7 1
Numerical optimization
132
7.1
The golden section search method
132
7.2
Newton-Raphson
135
7.3
The Nelder-Mead simplex method
138
7.4
Built-in functions
142
viii
1 CONTENTS
7.5
Linear programming
142
7.5.1
Solving linear programming problems in
R
145
7.5.2
Maximization and other kinds of constraints
145
7.5.3
Special situations
146
7.5.4
Unrestricted variables
149
7.5.5
Integer programming
150
7.5.6
Alternatives to
lp
( )
151
7.5.7
Quadratic programming
151
Chapter exercises
157
Appendix
Review of random variables
і
and distributions
158
1
index
161
This is the only introduction you'll need to start programming in R, the open-source
language that is free to download and lets you adapt the source code for your own
requirements. Co-written by one of the RCore Development Team, and by an
established
R
author, this book comes with real
R
code that complies with the
standards of the language.
•
Self-contained first course in statistical computing
•
Accessible to any student familiar with university-level calculus
•
The basics of
R
syntax and statistical graphics are explained, and elementary
programming is discussed
•
Programming applications in simulation and optimization as well as numerical
linear algebra are introduced
•
Many worked examples with notes on "understanding the code"
•
All examples are drawn from statistical applications
•
End-of-chapter review questions plus over
150
exercises; data sets and solutions
all available on web |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author | Braun, W. John 1963- Murdoch, Duncan J. 1959- |
| author_GND | (DE-588)13396440X (DE-588)1117735443 |
| author_facet | Braun, W. John 1963- Murdoch, Duncan J. 1959- |
| author_role | aut aut |
| author_sort | Braun, W. John 1963- |
| author_variant | w j b wj wjb d j m dj djm |
| building | Verbundindex |
| bvnumber | BV022945077 |
| callnumber-first | Q - Science |
| callnumber-label | QA276 |
| callnumber-raw | QA276.45.R3 |
| callnumber-search | QA276.45.R3 |
| callnumber-sort | QA 3276.45 R3 |
| callnumber-subject | QA - Mathematics |
| classification_rvk | QH 231 ST 250 ST 601 SK 830 |
| ctrlnum | (OCoLC)254096826 (DE-599)BVBBV022945077 |
| dewey-full | 519.502855133 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.502855133 |
| dewey-search | 519.502855133 |
| dewey-sort | 3519.502855133 |
| dewey-tens | 510 - Mathematics |
| discipline | Informatik Mathematik Wirtschaftswissenschaften |
| discipline_str_mv | Informatik Mathematik Wirtschaftswissenschaften |
| edition | 1. publ. |
| format | Book |
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| id | DE-604.BV022945077 |
| illustrated | Illustrated |
| index_date | 2024-07-02T18:59:28Z |
| indexdate | 2024-07-09T21:08:16Z |
| institution | BVB |
| isbn | 9780521694247 9780521872652 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-016149658 |
| oclc_num | 254096826 |
| open_access_boolean | |
| owner | DE-473 DE-BY-UBG DE-945 DE-355 DE-BY-UBR DE-92 DE-188 |
| owner_facet | DE-473 DE-BY-UBG DE-945 DE-355 DE-BY-UBR DE-92 DE-188 |
| physical | X, 163 S. Illustrationen |
| publishDate | 2007 |
| publishDateSearch | 2007 |
| publishDateSort | 2007 |
| publisher | Cambridge Univ. Press |
| record_format | marc |
| spelling | Braun, W. John 1963- Verfasser (DE-588)13396440X aut A first course in statistical programming with R W. John Braun and Duncan J. Murdoch 1. publ. Cambridge [u.a.] Cambridge Univ. Press 2007 X, 163 S. Illustrationen txt rdacontent n rdamedia nc rdacarrier Programmeren (computers) gtt R (computerprogramma) gtt Datenverarbeitung Statistik R (Computer program language) Statistics Data processing Statistik (DE-588)4056995-0 gnd rswk-swf R Programm (DE-588)4705956-4 gnd rswk-swf Statistik (DE-588)4056995-0 s R Programm (DE-588)4705956-4 s DE-604 Murdoch, Duncan J. 1959- Verfasser (DE-588)1117735443 aut Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016149658&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Regensburg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016149658&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
| spellingShingle | Braun, W. John 1963- Murdoch, Duncan J. 1959- A first course in statistical programming with R Programmeren (computers) gtt R (computerprogramma) gtt Datenverarbeitung Statistik R (Computer program language) Statistics Data processing Statistik (DE-588)4056995-0 gnd R Programm (DE-588)4705956-4 gnd |
| subject_GND | (DE-588)4056995-0 (DE-588)4705956-4 |
| title | A first course in statistical programming with R |
| title_auth | A first course in statistical programming with R |
| title_exact_search | A first course in statistical programming with R |
| title_exact_search_txtP | A first course in statistical programming with R |
| title_full | A first course in statistical programming with R W. John Braun and Duncan J. Murdoch |
| title_fullStr | A first course in statistical programming with R W. John Braun and Duncan J. Murdoch |
| title_full_unstemmed | A first course in statistical programming with R W. John Braun and Duncan J. Murdoch |
| title_short | A first course in statistical programming with R |
| title_sort | a first course in statistical programming with r |
| topic | Programmeren (computers) gtt R (computerprogramma) gtt Datenverarbeitung Statistik R (Computer program language) Statistics Data processing Statistik (DE-588)4056995-0 gnd R Programm (DE-588)4705956-4 gnd |
| topic_facet | Programmeren (computers) R (computerprogramma) Datenverarbeitung Statistik R (Computer program language) Statistics Data processing R Programm |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016149658&sequence=000003&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016149658&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
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