Ivo Dinov
UCLA Statistics, Neurology, LONI
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Statistics 130D
Winter 2007

Statistical Programming, Computation, and Visualization in C/C++/Java


Project Assignment Policy:

Textbook: Class notes + textbooks to be announced
    Tentative schedule of topics to be covered
  1. Review (2 wks):
        - Computer Systems, Writing, compiling, making, packaging,
            distributing and running programs/software
        - Variables and assignments, Input/Output, Data types and
             - Procedural (structured) vs. object oriented programming
        - Classes, methods, abstract data types
        - Overloading (functions & classes)
        - Call-by-value vs. call-by-reference
        - I/O Streams
        - Multidimensional Arrays
        - Strings
        - Pointers, dynamic arrays
        - Recursion
  2. Template (classes and methods) (1 wk)
        - Algorithm and Data abstraction
        HW1: Create a simple software package that reads in an image,
            blurs the image and saves out the result.
  3. Linked lists, graphs (trees) (1 wk)
        - Traversing
        - Sorting
  4. Visualization ToolKit (VTK), (1 wks) & R/C++ Integration
        HW2: Create a GUI that reads in a volume (or a series of images) processes these by temporal (index) moving average, displays the original and the filtered volume and saves the latter out.
  5. Inheritance (1 wk)
        - Constructors, derived classes, polymorphisms
  6. Exception handling mechanisms (1 wk)
        HW3: Extend and add more processing tools, more stability (incl. exception handling) and more portability to the previous package.
  7. Statistical Computing (2 wks)
        - Data stat summaries
        - model fitting
        - others
  8. Data Filtering (2 wks)
        HW4: Extend and add a variety of statistical analysis tools to your previous package (e.g. intensity-based image segmentation, wavelet shrinkage, Fourier decomposition).

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