課程目錄:Introduction to R with Time Series Analysis培訓
4401 人關注
(78637/99817)
課程大綱:

         Introduction to R with Time Series Analysis培訓

 

 

 

Introduction and preliminaries
Making R more friendly, R and available GUIs
Rstudio
Related software and documentation
R and statistics
Using R interactively
An introductory session
Getting help with functions and features
R commands, case sensitivity, etc.
Recall and correction of previous commands
Executing commands from or diverting output to a file
Data permanency and removing objects
Simple manipulations; numbers and vectors
Vectors and assignment
Vector arithmetic
Generating regular sequences
Logical vectors
Missing values
Character vectors
Index vectors; selecting and modifying subsets of a data set
Other types of objects
Objects, their modes and attributes
Intrinsic attributes: mode and length
Changing the length of an object
Getting and setting attributes
The class of an object
Arrays and matrices
Arrays
Array indexing. Subsections of an array
Index matrices
The array() function
The outer product of two arrays
Generalized transpose of an array
Matrix facilities
Matrix multiplication
Linear equations and inversion
Eigenvalues and eigenvectors
Singular value decomposition and determinants
Least squares fitting and the QR decomposition
Forming partitioned matrices, cbind() and rbind()
The concatenation function, (), with arrays
Frequency tables from factors
Lists and data frames
Lists
Constructing and modifying lists
Concatenating lists
Data frames
Making data frames
attach() and detach()
Working with data frames
Attaching arbitrary lists
Managing the search path
Data manipulation
Selecting, subsetting observations and variables
Filtering, grouping
Recoding, transformations
Aggregation, combining data sets
Character manipulation, stringr package
Reading data
Txt files
CSV files
XLS, XLSX files
SPSS, SAS, Stata,… and other formats data
Exporting data to txt, csv and other formats
Accessing data from databases using SQL language
Probability distributions
R as a set of statistical tables
Examining the distribution of a set of data
One- and two-sample tests
Grouping, loops and conditional execution
Grouped expressions
Control statements
Conditional execution: if statements
Repetitive execution: for loops, repeat and while
Writing your own functions
Simple examples
Defining new binary operators
Named arguments and defaults
The '...' argument
Assignments within functions
More advanced examples
Efficiency factors in block designs
Dropping all names in a printed array
Recursive numerical integration
Scope
Customizing the environment
Classes, generic functions and object orientation
Graphical procedures
High-level plotting commands
The plot() function
Displaying multivariate data
Display graphics
Arguments to high-level plotting functions
Basic visualisation graphs
Multivariate relations with lattice and ggplot package
Using graphics parameters
Graphics parameters list
Time series Forecasting
Seasonal adjustment
Moving average
Exponential smoothing
Extrapolation
Linear prediction
Trend estimation
Stationarity and ARIMA modelling
Econometric methods (casual methods)
Regression analysis
Multiple linear regression
Multiple non-linear regression
Regression validation
Forecasting from regression

主站蜘蛛池模板: 亚洲国产欧美国产综合久久| 一本色综合网久久| 天天做天天爱天天爽综合区| 国产精品九九久久精品女同亚洲欧美日韩综合区| 91精品国产综合久久四虎久久无码一级| 欧美日韩国产综合一区二区三区| 久久午夜综合久久| 中文字幕乱码人妻综合二区三区| 亚洲欧美日韩国产综合| 激情综合色五月丁香六月亚洲| 五月天激情综合| 日日AV色欲香天天综合网| senima亚洲综合美女图| 狠狠色丁香久久婷婷综合五月| 亚洲综合精品香蕉久久网97| 亚洲综合色成在线播放| 无码专区久久综合久中文字幕| 亚洲国产综合人成综合网站| 93精91精品国产综合久久香蕉| 美国十次狠狠色综合| 久久综合九色欧美综合狠狠| 国产欧美日韩综合自拍| 久久婷婷五月综合97色一本一本| 国产色综合天天综合网| 亚洲综合AV在线在线播放| 亚洲国产精品成人AV无码久久综合影院| 无码国内精品久久综合88| 狠狠色伊人久久精品综合网| 亚洲综合精品网站在线观看| 狠狠亚洲婷婷综合色香五月排名| 亚洲国产一成久久精品国产成人综合| 91精品国产综合久久四虎久久无码一级| 久久久久久久综合综合狠狠| 色噜噜狠狠色综合日日| 亚洲五月综合缴情在线观看| 天天做天天爱天天综合网2021| 亚洲伊人久久综合影院| 色综合天天做天天爱| 97se亚洲国产综合自在线| 国产综合成人色产三级高清在线精品发布| 亚洲人成综合网站7777香蕉|