R cookbook: [proven recipes for data analysis, statistics, and graphics]
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Beijing [u.a.]
O'Reilly
2011
|
| Ausgabe: | 1. ed. |
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XVIII, 413 S. graph. Darst. |
| ISBN: | 9780596809157 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV037371725 | ||
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| 005 | 20160803 | ||
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| 020 | |a 9780596809157 |9 978-0-596-80915-7 | ||
| 035 | |a (OCoLC)706905101 | ||
| 035 | |a (DE-599)HBZHT016722300 | ||
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| 041 | 0 | |a eng | |
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| 084 | |a ST 250 |0 (DE-625)143626: |2 rvk | ||
| 100 | 1 | |a Teetor, Paul |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a R cookbook |b [proven recipes for data analysis, statistics, and graphics] |c Paul Teetor |
| 250 | |a 1. ed. | ||
| 264 | 1 | |a Beijing [u.a.] |b O'Reilly |c 2011 | |
| 300 | |a XVIII, 413 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 650 | 0 | 7 | |a R |g Programm |0 (DE-588)4705956-4 |2 gnd |9 rswk-swf |
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| 856 | 4 | 2 | |m Digitalisierung UB Passau |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022525051&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-022525051 | |
Datensatz im Suchindex
| DE-BY-862_location | 2000 |
|---|---|
| DE-BY-FWS_call_number | 2000/ST 250 R01 T258 |
| DE-BY-FWS_katkey | 560465 |
| DE-BY-FWS_media_number | 083000513370 |
| _version_ | 1806527566120484864 |
| adam_text |
Table
of
Contents
Preface
. xiii
1.
Getting Started and Getting Help
.1
1.1
Downloading and Installing
R
2
1.2
Starting
R
4
1.3
Entering Commands
7
1.4
Exiting from
R
8
1.5
Interrupting
R
9
1.6
Viewing the Supplied Documentation
10
1.7
Getting Help on a Function
11
1.8
Searching the Supplied Documentation
13
1.9
Getting Help on a Package
14
1.10
Searching the Web for Help
16
1.11
Finding Relevant Functions and Packages
18
1.12
Searching the Mailing Lists
19
1.13
Submitting Questions to the Mailing Lists
20
2.
Some Basics
.23
2.1
Printing Something
23
2.2
Setting Variables
25
2.3
Listing Variables
26
2.4
Deleting Variables
27
2.5
Creating a Vector
28
2.6
Computing Basic Statistics
30
2.7
Creating Sequences
32
2.8
Comparing Vectors
34
2.9
Selecting Vector Elements
35
2.10
Performing Vector Arithmetic
38
2.11
Getting Operator Precedence Right
40
2.12
Defining a Function
41
2.13
Typing Less and Accomplishing More
43
2.14
Avoiding Some Common Mistakes
46
3.
Navigating the Software
.51
3.1
Getting and Setting the Working Directory
51
3.2
Saving Your Workspace
52
3.3
Viewing Your Command History
53
3.4
Saving the Result of the Previous Command
53
3.5
Displaying the Search Path
54
3.6
Accessing the Functions in a Package
55
3.7
Accessing Built-in
Datasets
57
3.8
Viewing the List of Installed Packages
58
3.9
Installing Packages from
CRAN
59
3.10
Setting a Default
CRAN
Mirror
61
3.11
Suppressing the Startup Message
62
3.12
Running a Script
62
3.13
Running a Batch Script
63
3.14
Getting and Setting Environment Variables
66
3.15
Locating the
R
Home Directory
67
3.16
Customizing
R
68
4.
Input and Output
. 71
4.1
Entering Data from the Keyboard
72
4.2
Printing Fewer Digits (or More Digits)
73
4.3
Redirecting Output to a File
74
4.4
Listing Files
75
4.5
Dealing with "Cannot Open File" in Windows
76
4.6
Reading Fixed-Width Records
77
4.7
Reading Tabular Data Files
78
4.8
Reading from CSV Files
80
4.9
Writing to CSV Files
82
4.10
Reading Tabular or CSV Data from the Web
83
4.11
Reading Data from HTML Tables
84
4.12
Reading Files with a Complex Structure
86
4.13
Reading from MySQL Databases
89
4.14
Saving and Transporting Objects
92
5.
Data Structures
.95
5.1
Appending Data to a Vector
101
5.2
Inserting Data into a Vector
103
5.3
Understanding the Recycling Rule
103
5.4
Creating a Factor (Categorical Variable)
105
5.5
Combining Multiple Vectors into One Vector and a Factor
107
5.6
Creating a List
108
vi
I Table of Contents
5.7
Selecting List
Elements
by
Position 109
5.8
Selecting List Elements by Name 111
5.9
Building a Name/Value Association List
112
5.10
Removing an Element from a List
114
5.11
Flatten a List into a Vector
115
5.12
Removing NULL Elements from a List
116
5.13
Removing List Elements Using a Condition
117
5.14
Initializing a Matrix
118
5.15
Performing Matrix Operations
119
5.16
Giving Descriptive Names to the Rows and Columns of a Matrix
120
5.17
Selecting One Row or Column from a Matrix
121
5.18
Initializing a Data Frame from Column Data
122
5.19
Initializing a Data Frame from Row Data
123
5.20
Appending Rows to a Data Frame
125
5.21
Preallocating a Data Frame
126
5.22
Selecting Data Frame Columns by Position
127
5.23
Selecting Data Frame Columns by Name
131
5.24
Selecting Rows and Columns More Easily
132
5.25
Changing the Names of Data Frame Columns
133
5.26
Editing a Data Frame
135
5.27
Removing NAs from a Data Frame
136
5.28
Excluding Columns by Name
137
5.29
Combining Two Data Frames
138
5.30
Merging Data Frames by Common Column
140
5.31
Accessing Data Frame Contents More Easily
141
5.32
Converting One Atomic Value into Another
143
5.33
Converting One Structured Data Type into Another
144
6.
Data Transformations
. 147
6.1
Splitting a Vector into Groups
148
6.2
Applying a Function to Each List Element
149
6.3
Applying a Function to Every Row
151
6.4
Applying a Function to Every Column
152
6.5
Applying a Function to Groups of Data
154
6.6
Applying a Function to Groups of Rows
156
6.7
Applying a Function to Parallel Vectors or Lists
158
7.
StringsandDates
.161
7.1
Getting the Length of a String
163
7.2
Concatenating Strings
163
7.3
Extracting Substrings
164
7.4
Splitting a String According to a Delimiter
165
7.5
Replacing Substrings
166
Table of Contents I
vii
7.6
Seeing the
Special
Characters in a String
167
7.7
Generating All Pairwise Combinations of Strings
168
7.8
Getting the Current Date
169
7.9
Converting a String into a Date
170
7.10
Converting a Date into a String
171
7.11
Converting Year, Month, and Day into a Date
172
7.12
Getting the Julian Date
173
7.13
Extracting the Parts of a Date
174
7.14
Creating a Sequence of Dates
175
8.
Probability
. 177
8.1
Counting the Number of Combinations
179
8.2
Generating Combinations
180
8.3
Generating Random Numbers
180
8.4
Generating Reproducible Random Numbers
182
8.5
Generating a Random Sample
183
8.6
Generating Random Sequences
184
8.7
Randomly Permuting a Vector
185
8.8
Calculating Probabilities for Discrete Distributions
186
8.9
Calculating Probabilities for Continuous Distributions
188
8.10
Converting Probabilities to Quantiles
189
8.11
Plotting a Density Function
190
9.
General Statistics
. 195
9.1
Summarizing Your Data
197
9.2
Calculating Relative Frequencies
199
9.3
Tabulating Factors and Creating Contingency Tables
200
9.4
Testing Categorical Variables for Independence
201
9.5
Calculating Quantiles (and Quartiles) of
a
Dataset
201
9.6
Inverting a Quantile
202
9.7
Converting Data to Z-Scores
203
9.8
Testing the Mean of a Sample (t Test)
203
9.9
Forming a Confidence Interval for a Mean
205
9.10
Forming a Confidence Interval for a Median
206
9.11
Testing a Sample Proportion
207
9.12
Forming a Confidence Interval for a Proportion
208
9.13
Testing for Normality
209
9.14
Testing for Runs
210
9.15
Comparing the Means of Two Samples
212
9.16
Comparing the Locations of Two Samples Nonparametrically
213
9.17
Testing a Correlation for Significance
215
9.18
Testing Groups for Equal Proportions
216
9.19
Performing Pairwise Comparisons Between Group Means
218
viii
I Table of Contents
9.20
Testing Two Samples for the Same Distribution
219
10.
Graphics
.221
10.1
Creating a Scatter Plot
223
10.2
Adding a Title and Labels
225
10.3
Adding a Grid
226
10.4
Creating a Scatter Plot of Multiple Groups
227
10.5
Adding a Legend
229
10.6
Plotting the Regression Line of a Scatter Plot
231
10.7
Plotting All Variables Against All Other Variables
233
10.8
Creating One Scatter Plot for Each Factor Level
233
10.9
Creating a Bar Chart
236
10.10
Adding Confidence Intervals to a Bar Chart
237
10.11
Coloring a Bar Chart
239
10.12
Plotting a Line from
χ
and
y
Points
241
10.13
Changing the Type, Width, or Color of a Line
242
10.14
Plotting Multiple
Datasets
243
10.15
Adding Vertical or Horizontal Lines
245
10.16
Creating a Box Plot
246
10.17
Creating One Box Plot for Each Factor Level
247
10.18
Creating a Histogram
248
10.19
Adding a Density Estimate to a Histogram
250
10.20
Creating a Discrete Histogram
252
10.21
Creating a Normal Quantile-Quantile (Q-Q) Plot
252
10.22
Creating Other Quantile-Quantile Plots
254
10.23
Plotting a Variable in Multiple Colors
256
10.24
Graphing a Function
258
10.25
Pausing Between Plots
259
10.26
Displaying Several Figures on One Page
260
10.27
Opening Additional Graphics Windows
262
10.28
Writing Your Plot to a File
263
10.29
Changing Graphical Parameters
264
11.
Linear Regression and ANOVA
.267
11.1
Performing Simple Linear Regression
269
11.2
Performing Multiple Linear Regression
270
11.3
Getting Regression Statistics
272
11.4
Understanding the Regression Summary
275
11.5
Performing Linear Regression Without an Intercept
278
11.6
Performing Linear Regression with Interaction Terms
279
11.7
Selecting the Best Regression Variables
281
11.8
Regressing on a Subset of Your Data
284
11.9
Using an Expression Inside a Regression Formula
285
Table of Contents I
ix
11.10
Regressing on a Polynomial
286
11.11
Regressing on Transformed Data
287
11.12
Finding the Best Power Transformation
(Box
-Сох
Procedure)
289
11.13
Forming Confidence Intervals for Regression Coefficients
292
11.14
Plotting Regression Residuals
293
11.15
Diagnosing a Linear Regression
293
11.16
Identifying Influential Observations
296
11.17
Testing Residuals for Autocorrelation (Durbin-Watson Test)
298
11.18
Predicting New Values
300
11.19
Forming Prediction Intervals
301
11.20
Performing One-Way ANOVA
302
11.21
Creating an Interaction Plot
303
11.22
Finding Differences Between Means of Groups
304
11.23
Performing Robust ANOVA (Kruskal-Wallis Test)
308
11.24
Comparing Models by Using ANOVA
309
12.
Useful Tricks
. 313
12.1
Peeking at Your Data
313
12.2
Widen Your Output
314
12.3
Printing the Result of an Assignment
315
12.4
Summing Rows and Columns
315
12.5
Printing Data in Columns
316
12.6
Binning Your Data
317
12.7
Finding the Position of a Particular Value
318
12.8
Selecting Every nth Element of a Vector
319
12.9
Finding Pairwise
Minimums
or
Maximums 320
12.10
Generating All Combinations of Several Factors
321
12.11
Flatten a Data Frame
322
12.12
Sorting a Data Frame
323
12.13
Sorting by Two Columns
324
12.14
Stripping Attributes from a Variable
325
12.15
Revealing the Structure of an Object
326
12.16
Timing Your Code
329
12.17
Suppressing Warnings and Error Messages
329
12.18
Taking Function Arguments from a List
331
12.19
Defining Your Own Binary Operators
332
13.
Beyond Basic Numerics and Statistics
. 335
13.1
Minimizing or Maximizing a Single-Parameter Function
335
13.2
Minimizing or Maximizing a Multiparameter Function
336
13.3
Calculating Eigenvalues and Eigenvectors
338
13.4
Performing Principal Component Analysis
338
13.5
Performing Simple Orthogonal Regression
340
χ
| Table of Contents
13.6
Finding Clusters in Your Data
342
13.7
Predicting a Binary-Valued Variable (Logistic Regression)
345
13.8
Bootstrapping a Statistic
346
13.9
Factor Analysis
349
14.
Time Series Analysis
.355
14.1
Representing Time Series Data
356
14.2
Plotting Time Series Data
359
14.3
Extracting the Oldest or Newest Observations
361
14.4
Subsetting a Time Series
363
14.5
Merging Several Time Series
364
14.6
Filling or Padding a Time Series
366
14.7
Lagging a Time Series
368
14.8
Computing Successive Differences
369
14.9
Performing Calculations on Time Series
370
14.10
Computing a Moving Average
372
14.11
Applying a Function by Calendar Period
373
14.12
Applying a Rolling Function
375
14.13
Plotting the Autocorrelation Function
376
14.14
Testing a Time Series for Autocorrelation
377
14.15
Plotting the Partial Autocorrelation Function
378
14.16
Finding Lagged Correlations Between Two Time Series
379
14.17
Detrending a Time Series
382
14.18
Fitting an ARIMA Model
383
14.19
Removing Insignificant ARIMA Coefficients
386
14.20
Running Diagnostics on an ARIMA Model
387
14.21
Making Forecasts from an ARIMA Model
389
14.22
Testing for Mean Reversion
391
14.23
Smoothing a Time Series
393
Index
.397
Table of Contents I
xi |
| any_adam_object | 1 |
| author | Teetor, Paul |
| author_facet | Teetor, Paul |
| author_role | aut |
| author_sort | Teetor, Paul |
| author_variant | p t pt |
| building | Verbundindex |
| bvnumber | BV037371725 |
| classification_rvk | MR 2200 SK 850 ST 250 |
| ctrlnum | (OCoLC)706905101 (DE-599)HBZHT016722300 |
| discipline | Informatik Soziologie Mathematik |
| edition | 1. ed. |
| format | Book |
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| id | DE-604.BV037371725 |
| illustrated | Illustrated |
| indexdate | 2024-08-05T08:22:21Z |
| institution | BVB |
| isbn | 9780596809157 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-022525051 |
| oclc_num | 706905101 |
| open_access_boolean | |
| owner | DE-11 DE-945 DE-19 DE-BY-UBM DE-824 DE-739 DE-2070s DE-188 DE-N2 DE-473 DE-BY-UBG DE-29 DE-83 DE-384 DE-703 DE-706 DE-355 DE-BY-UBR DE-862 DE-BY-FWS DE-1051 DE-521 |
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| physical | XVIII, 413 S. graph. Darst. |
| publishDate | 2011 |
| publishDateSearch | 2011 |
| publishDateSort | 2011 |
| publisher | O'Reilly |
| record_format | marc |
| spellingShingle | Teetor, Paul R cookbook [proven recipes for data analysis, statistics, and graphics] R Programm (DE-588)4705956-4 gnd |
| subject_GND | (DE-588)4705956-4 |
| title | R cookbook [proven recipes for data analysis, statistics, and graphics] |
| title_auth | R cookbook [proven recipes for data analysis, statistics, and graphics] |
| title_exact_search | R cookbook [proven recipes for data analysis, statistics, and graphics] |
| title_full | R cookbook [proven recipes for data analysis, statistics, and graphics] Paul Teetor |
| title_fullStr | R cookbook [proven recipes for data analysis, statistics, and graphics] Paul Teetor |
| title_full_unstemmed | R cookbook [proven recipes for data analysis, statistics, and graphics] Paul Teetor |
| title_short | R cookbook |
| title_sort | r cookbook proven recipes for data analysis statistics and graphics |
| title_sub | [proven recipes for data analysis, statistics, and graphics] |
| topic | R Programm (DE-588)4705956-4 gnd |
| topic_facet | R Programm |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=3641052&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=022525051&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT teetorpaul rcookbookprovenrecipesfordataanalysisstatisticsandgraphics |
Beschreibung
Sonderstandort Fakultät
| Signatur: |
2000 ST 250 R01 T258 |
|---|---|
| Exemplar 1 | nicht ausleihbar Checked out – Rückgabe bis: 31.12.2099 Vormerken |