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      課程目錄:Introduction to R with Time Series Analysis培訓
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               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

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