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Andrew
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Updates for Mk 28.3
1 parent 1cdb9f0 commit d2aeab0

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‎Examples/bonus/debt_compression_question.ipynb

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‎Examples/correg/lmm_notebook.ipynb

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"name": "python",
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"version": "3.9.1"
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"version": "3.8.10"
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‎Examples/correg/quantile_linreg_easy.ipynb

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‎Examples/correg/quantile_linreg_pandas.ipynb

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‎Examples/fit/dim2_spline_ts_sctr.ipynb

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‎Examples/mv/iris.ipynb

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‎Examples/opt/bounds_quasi_func_easy.ipynb

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‎Examples/simple/Simple.ipynb renamed to ‎Examples/simple_exception/Simple.ipynb

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‎Examples/simple/SimpleException.ipynb renamed to ‎Examples/simple_exception/SimpleException.ipynb

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‎Examples/tsa/cp_pelt_new.ipynb

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‎hands-on-exercises/fix_this-q.ipynb

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"cell_type": "markdown",
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"![title](../NAG_logo.png)\n",
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"# Principal component analysis\n",
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"\n",
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"The following program uses the routine `mv.prin_comp` to performs principal component analysis on a variance-covariance matrix, which consists of _the first two columns_ of the following matrix `x`. Use `help` and follow the error messages to fix the program. "
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"The following program uses the routine `mv.prin_comp` to performs principal component analysis on a variance-covariance matrix, which consists of _the first two columns_ of the following matrix `x`. Use `help` and follow the error messages to fix the program.\n",
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"\n",
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"## hints\n",
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"\n",
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" 1. All arrays have to be contiguous (there is a speed advantage if they are also column-major (Fortran-like))\n",
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" 2. Documentation for mv.prin_comp can be requested inside this notebook by using `?mv.prin_comp`\n",
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" 3. Make sure that `s` is of the right length\n",
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" 3. Make sure that the returned object from `prin_comp` as a `stat` member\n",
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" 4. See also the `iris` PCA example notebook"
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{
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‎hands-on-exercises/implied-volatility-q.ipynb

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"![title](../nag_logo.png)\n",
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"![title](../NAG_logo.png)\n",
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"\n",
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"# Exercises - Implied Volatility\n",
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"- $\\sigma$ = 0.09\n",
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"You should get an answer of 12.35008695."
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‎hands-on-exercises/odes-q.ipynb

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"# Exercises - Ordinary Differential Equations\n",
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‎hands-on-exercises/opt-q.ipynb

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‎hands-on-exercises/option-pricing-q.ipynb

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‎hands-on-exercises/polyfit-q.ipynb

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‎hands-on-exercises/reg-q.ipynb

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"cell_type": "markdown",
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"# Regression\n",
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‎hands-on-exercises/short-q.ipynb

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"# Exercises - short questions\n",
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