Muutke küpsiste eelistusi

E-raamat: Introductory Fisheries Analyses with R

(Northland College, Ashland, Wisconsin, USA)
  • Formaat - PDF+DRM
  • Hind: 64,99 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

A How-To Guide for Conducting Common Fisheries-Related Analyses in R

Introductory Fisheries Analyses with R provides detailed instructions on performing basic fisheries stock assessment analyses in the R environment. Accessible to practicing fisheries scientists as well as advanced undergraduate and graduate students, the book demonstrates the flexibility and power of R, offers insight into the reproducibility of script-based analyses, and shows how the use of R leads to more efficient and productive work in fisheries science.

The first three chapters present a minimal introduction to the R environment that builds a foundation for the fisheries-specific analyses in the remainder of the book. These chapters help you become familiar with R for basic fisheries analyses and graphics.

Subsequent chapters focus on methods to analyze age comparisons, age-length keys, size structure, weight-length relationships, condition, abundance (from capture-recapture and depletion data), mortality rates, individual growth, and the stock-recruit relationship. The fundamental statistical methods of linear regression, analysis of variance (ANOVA), and nonlinear regression are demonstrated within the contexts of these common fisheries analyses. For each analysis, the author completely explains the R functions and provides sufficient background information so that you can confidently implement each method.

Web Resource The authors website at http://derekogle.com/IFAR/ includes the data files and R code for each chapter, enabling you to reproduce the results in the book as well as create your own scripts. The site also offers supplemental code for more advanced analyses and practice exercises for every chapter.
Preface xiii
Author xix
1 (Very Brief) Introduction to R Basics
1(20)
1.1 Why R for Fisheries Scientists?
1(1)
1.2 Installing R and RStudio
2(1)
1.3 Packages
2(1)
1.4 Prompts, Expressions, and Comments
3(1)
1.5 Objects
4(1)
1.6 Functions
5(1)
1.7 Data Storage
6(7)
1.8 More with Functions
13(3)
1.9 Looping
16(2)
1.10 Saving Results
18(1)
1.11 Getting Help
18(3)
2 Loading Data and Basic Manipulations
21(30)
2.1 Loading Data into R
21(4)
2.2 Basic Data Manipulations
25(10)
2.3 Joining Data.Frames
35(5)
2.4 Rearranging Data.Frames
40(2)
2.5 New Data.frame from Aggregation
42(6)
2.6 Exporting Data.Frames to External Data Files
48(1)
2.7 Further Considerations
49(2)
3 Plotting Fundamentals
51(24)
3.1 Scatterplots
52(4)
3.2 Line Plots
56(2)
3.3 Histograms
58(2)
3.4 Bar Plots
60(3)
3.5 Fitted Model Plots
63(3)
3.6 Some Finer Control of Plots
66(7)
3.7 Saving or Exporting Plots
73(2)
4 Age Comparisons
75(12)
4.1 Data Requirements
76(1)
4.2 Age Bias Plot
76(3)
4.3 Bias Metrics
79(4)
4.4 Precision Metrics
83(2)
4.5 Further Considerations
85(2)
5 Age-Length Keys
87(20)
5.1 Foundational Background
87(2)
5.2 Constructing an Age-Length Key
89(5)
5.3 Visualizing an Age-Length Key
94(2)
5.4 Apply an Age-Length Key
96(6)
5.5 Among Group Statistical Comparisons
102(1)
5.6 Further Considerations
103(4)
6 Size Structure
107(24)
6.1 Data Requirements
108(1)
6.2 Length Frequency
109(4)
6.3 Proportional Size Distribution (PSD)
113(9)
6.4 Among Group Statistical Comparisons
122(4)
6.5 Further Considerations
126(5)
7 Weight-Length Relationships
131(22)
7.1 Data Requirements
132(1)
7.2 Weight-Length Model
133(1)
7.3 Fitting Linear Regressions
134(6)
7.4 Among Group Statistical Comparisons
140(8)
7.5 Further Considerations
148(5)
8 Condition
153(16)
8.1 Data Requirements
154(1)
8.2 Condition Metrics
154(5)
8.3 Among Group Statistical Comparisons
159(7)
8.4 Further Considerations
166(3)
9 Abundance from Capture-Recapture Data
169(24)
9.1 Data Requirements
169(4)
9.2 Closed Population, Single Recapture
173(3)
9.3 Closed Population, Multiple Recaptures
176(7)
9.4 Open Populations
183(5)
9.5 Further Considerations
188(5)
10 Abundance from Depletion Data
193(10)
10.1 Leslie and DeLury Methods
193(4)
10.2 K-Pass Removal Methods
197(6)
11 Mortality Rates
203(18)
11.1 Total Mortality Definitions
203(1)
11.2 Total Mortality from Catch Curve Data
204(9)
11.3 Total Mortality from Capture-Recapture Data
213(3)
11.4 Mortality Components
216(2)
11.5 Further Considerations
218(3)
12 Individual Growth
221(30)
12.1 Data Requirements
222(1)
12.2 Growth Functions
222(2)
12.3 Fitting Nonlinear Regressions
224(11)
12.4 Among Group Statistical Comparisons
235(10)
12.5 Typical Model Fitting Problems
245(3)
12.6 Further Considerations
248(3)
13 Recruitment
251(32)
13.1 Stock-Recruitment Relationships
252(11)
13.2 Spawning Potential Ratio
263(7)
13.3 Year-Class Strength
270(9)
13.4 Further Considerations
279(4)
References 283(22)
Subject Index 305(6)
R Functions (Demonstrated) Index 311(4)
R Functions (Mentioned) Index 315(2)
Scientific Names 317
Derek H. Ogle is a professor of mathematical sciences and natural resources at Northland College, where he teaches statistics and fisheries science courses and has received awards for teaching, scholarly work, service, and assessment activities. Dr. Ogle maintains the fishR website, which is dedicated to sharing information on how to perform fisheries analyses in R. He earned a PhD in fisheries science from the University of Minnesota. His research interests include the population dynamics of invasive species and little-studied native species.