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Introduction to R with Time Series Analysis培训

 
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上课地点:【上海】:同济大学(沪西)/新城金郡商务楼(11号线白银路站) 【深圳分部】:电影大厦(地铁一号线大剧院站)/深圳大学成教院 【北京分部】:北京中山/福鑫大楼 【南京分部】:金港大厦(和燕路) 【武汉分部】:佳源大厦(高新二路) 【成都分部】:领馆区1号(中和大道) 【沈阳分部】:沈阳理工大学/六宅臻品 【郑州分部】:郑州大学/锦华大厦 【石家庄分部】:河北科技大学/瑞景大厦 【广州分部】:广粮大厦 【西安分部】:协同大厦
近开间(周末班/连续班/晚班):2018年3月18日
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课程大纲
 
  • 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
 

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