iLearn Macquarie
iLearn Macquarie
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ACST3060: AR(p) Time Series Models
Week 10 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We cover the AR(p) time series models. Specifically, we:
• Present a condition ensuring the weak stationarity of the process.
• Derive the expected value, variance and autocorrelations of the process (the latter being derived using the “Yule Walker” equations).
• Present rules to select the order “p” within an AR(p) model.
• Define “residuals” and “fitted values”.
• Discuss diagnostics to assess model fit.
• Discuss forecasting using an AR(p) model.
(Narrated by Dr Guillaume Boglioni)
Переглядів: 145

Відео

ACST3060: Archimedean Copulas
Переглядів 2532 місяці тому
Week 9 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis): we introduce Archimedean copulas. We derive the bivariate Gumbel and bivariate Clayton copula and discuss their properties. We briefly cover k-variate Archimedean copulas (for an arbitrary integer k } 2). (Narrated by Dr Guillaume Boglioni)
ACST3060: Other Copula Topics
Переглядів 1132 місяці тому
Week 9 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We cover two “small” copula topics (that did not fit neatly into previous sections): • Kendall’s Tau “shortcut” formula • Kendall’s distribution function (Narrated by Dr Guillaume Boglioni)
ACST3060: Copula Fitting in R
Переглядів 2252 місяці тому
Week 9 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We use R to fit a copula to a dataset. Specifically, we fit the Clayton copula to a bivariate dataset, and following different approaches: • Method that relies on the empirical Kendall’s Tau. • Maximum Likelihood where margins are estimated empirically, and separately from the copula. • Maximum Likelihood ...
ACST3060: Copula Fitting (Theory)
Переглядів 1692 місяці тому
Week 9 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis): we discuss, conceptually, how to fit copulas to multivariate data. A separate video will cover the “actual” fitting, done in R. (Narrated by Dr Guillaume Boglioni)
ACST3060: Tutorial on Week 8 - Dependence and Copulas
Переглядів 1703 місяці тому
Tutorial on Week 8 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We cover Exercises 8.3 to 8.7 of the Tutorial Booklet. (Narrated by Joel Denning)
ACST3060: Extreme Value Theory in R: Threshold Exceedances Method
Переглядів 2983 місяці тому
Week 7 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We use R to: • Simulate “threshold exceedances” data and check that their distribution is close to the Generalised Pareto distribution (GPD), as predicted by the Picklands-Balkema-de Haan Theorem. • Use the “mean excess plot” to choose a high threshold “u”, above which exceedances should be taken and fitte...
ACST3060: Extreme Value Theory in R: Block Maxima Method
Переглядів 3653 місяці тому
Week 7 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We use R to: • Compare the “tail weight” of the Normal to that of the Pareto distribution. • Simulate “maxima” data and check that their distribution is close to the Generalised Extreme Value distribution (GEV), as predicted by the Fisher-Tippett-Gnedenko Theorem. • Fit “maxima” data to the GEV and assess ...
ACST3060: Fitting Exceedances to the Generalised Pareto Distribution
Переглядів 2543 місяці тому
Week 6 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis): we explain how to fit threshold exceedances data to the Generalised Pareto Distribution. Specifically, we discuss two “rules of thumb” that can be used to select the “high threshold” (above which exceedances should be taken). (Narrated by Dr Guillaume Boglioni)
Extreme Value Theory: Threshold Exceedances Method
Переглядів 3403 місяці тому
Week 6 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis): we review the “Threshold Exceedances” method within Extreme Value Theory. Specifically, we introduce the “Generalised Pareto Distribution” (GPD) and present the important Picklands-Balkema-de Haan Theorem. (Narrated by Dr Guillaume Boglioni)
ACST3060: Kolmogorov-Smirnov Test in R
Переглядів 3454 місяці тому
Week 5 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). The Kolmogorov-Smirnov (KS) test is used to test the null hypothesis that a given sample of data comes from a specified distribution. We show, in R, how to compute the KS test statistic “from scratch”. This is a “programming exercise”, but we also show how to use the in-built R function “ks.test” to comput...
ACST3060: Discrete Convolutions in R
Переглядів 1674 місяці тому
Week 5 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We create, in R, functions to derive the distribution of discrete convolutions. More specifically: • The first function (which we call “convo”) can be used to find the probability mass function (PMF) of a convolution “S=X1 X2”, where X1 and X2 are discrete random variables (possibly with different distribu...
ACST3060: Simulations in R
Переглядів 2164 місяці тому
Week 5 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We show, in R, how to simulate random samples stemming from various probability distributions. We present examples on how to simulate from: • The Pareto distribution (which does not have a generator in base R). • A mixture distribution which is: Exponential(lambda) where “lambda” is itself a Gamma. • min(X...
ACST3060: Plotting Probability Functions in R
Переглядів 2264 місяці тому
Week 5 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis). We show, in R, how to plot several probability functions, namely: • The probability mass function (PMF) of a discrete distribution. • The probability density function (PDF) of a continuous distribution. • The cumulative distribution function (CDF). • The histogram of a sample. • The empirical CDF of a samp...
ACST3060: Risk-Adjusted Premium Principle
Переглядів 1474 місяці тому
Week 4 content (2024) for ACST3060 and ACST8085 (Quantitative Methods for Risk Analysis): we present the “Risk Adjusted Premium Principle”, which can be used to price an insurance risk “X”. We then check whether this principle satisfies all our premium axioms. We conclude it satisfies “non-negative loading”, “scale invariance”, “consistency” and “no ripoff”. However, it does not satisfy “additi...
ACST3060: Esscher Premium Principle
Переглядів 1774 місяці тому
ACST3060: Esscher Premium Principle
ACST3060: Approximations of the distribution of S within a Collective Risk Model
Переглядів 2034 місяці тому
ACST3060: Approximations of the distribution of S within a Collective Risk Model
ACST3060: Example of a Collective Risk Model with Excess of Loss Reinsurance
Переглядів 2004 місяці тому
ACST3060: Example of a Collective Risk Model with Excess of Loss Reinsurance
ACST3060: Optimisation in R
Переглядів 1424 місяці тому
ACST3060: Optimisation in R
ACST3060: Goodness of Fit
Переглядів 1454 місяці тому
ACST3060: Goodness of Fit
ACST3060: Bayes Estimators
Переглядів 1344 місяці тому
ACST3060: Bayes Estimators
ACST3060: Individual Risk Model
Переглядів 2014 місяці тому
ACST3060: Individual Risk Model
ACST3060: Sums of Random Variables
Переглядів 1974 місяці тому
ACST3060: Sums of Random Variables
iLearn Insights: A recap of key features for S2, 2024
Переглядів 1515 місяців тому
iLearn Insights: A recap of key features for S2, 2024
ACST3060: Common Continuous Distributions
Переглядів 816 місяців тому
ACST3060: Common Continuous Distributions
ACST3060: Mixture Distributions
Переглядів 2056 місяців тому
ACST3060: Mixture Distributions
ACST3060: Mixed Distributions
Переглядів 1146 місяців тому
ACST3060: Mixed Distributions
ACST3060: Common Discrete Distributions
Переглядів 906 місяців тому
ACST3060: Common Discrete Distributions
ACST3060: Moment Generating Function and Probability Generating Function
Переглядів 1856 місяців тому
ACST3060: Moment Generating Function and Probability Generating Function
Goodbye and good luck!
Переглядів 2536 місяців тому
Goodbye and good luck!

КОМЕНТАРІ

  • @jerryho6120
    @jerryho6120 Місяць тому

    Excellent explanation of the content! Thanks!

  • @Adameve-t7j
    @Adameve-t7j 2 місяці тому

    Thank you for this lecture video--it's amazingly discussed. But can I have the reference textbook for the mixture distribution?

  • @ideas.with.justiin
    @ideas.with.justiin 2 місяці тому

    Thank you for the copula video posted few days ago, the comment section is off there hence I am commenting here! (from South Africa🇿🇦)

  • @raymansingh2003
    @raymansingh2003 3 місяці тому

    waiting on the tutorial 8 video, will it be here?

  • @weitzun9691
    @weitzun9691 4 місяці тому

    Hey Guillaume, I have a question, @ 10:40 , I see you use the "Method of Moments" to get the estimator for the initial value (iv = c(a.mm, I.mm) ), did you have any article to support this method? Because I am searching around to get the support for my study, and I can't find it... You are the only one have the same approach as me to be honest...

  • @JudithDawes-y9u
    @JudithDawes-y9u 5 місяців тому

    I think the network connection diagram for discussion forums is cool!

  • @MillerQ-n9y
    @MillerQ-n9y 6 місяців тому

    I'm sold, just the expression on her face when I shot a thicker and substantial load was worth it, I used what I mentioned last month and after the first 3 weeks or so my volume visibly doubled, I just go'ogled Jan Venstaker's Shooting Ropes and the intensity has been insane!

  • @yousufrz1
    @yousufrz1 8 місяців тому

    what is the website called at 2:30

  • @charliefreeman9158
    @charliefreeman9158 Рік тому

    Promo sm

  • @LlamaLootLord
    @LlamaLootLord Рік тому

    the big question here is that, if they use the Similarity tool here, will it retain this information so that when the student comes to submit their work, will Turnitin Similarity report pick up 100% of the work as plagiarised due to the check done in Draft Coach?

    • @kirkabap9095
      @kirkabap9095 11 місяців тому

      In my case it happened to me today.

  • @muhammadshahab3436
    @muhammadshahab3436 Рік тому

    How to download my report please?

  • @mahedihasan-wt4mw
    @mahedihasan-wt4mw Рік тому

    Hi

  • @athulfgeirsson
    @athulfgeirsson Рік тому

    the darkest Aboriginal activist

  • @jenniferbenelli1861
    @jenniferbenelli1861 2 роки тому

    is it me or is there no sound?

  • @mrdhuuke5832
    @mrdhuuke5832 2 роки тому

    thank you very much

  • @InquisitorKryptman
    @InquisitorKryptman 2 роки тому

    Woo!

  • @alanapanman
    @alanapanman 2 роки тому

    i cant hear anything

  • @michaelmccarthy2819
    @michaelmccarthy2819 2 роки тому

    ᵖʳᵒᵐᵒˢᵐ

  • @alphakappalambda6191
    @alphakappalambda6191 2 роки тому

    「コンテンツを調整する必要があります」、

  • @ridinginryde
    @ridinginryde 2 роки тому

    Great video. The Shrimptons Creek Green Links draft master plan proposes some improvements around the skate park, hopefully removing some of the stigmas associated with it

  • @mantshonyanelent1652
    @mantshonyanelent1652 2 роки тому

    Important video unfortunately the video quality is not as good

  • @dolcevilla2923
    @dolcevilla2923 2 роки тому

    Shame this video is inaudible :(

  • @walrus7814
    @walrus7814 3 роки тому

    this is so silly

  • @nicknicols4747
    @nicknicols4747 3 роки тому

    so touching for an excellent video

  • @tamannabishnoi7590
    @tamannabishnoi7590 3 роки тому

    Keep going..great work

  • @dhruv29rules
    @dhruv29rules 3 роки тому

    Loved the attention towards details! Great going!!

  • @jasgeetkohli9417
    @jasgeetkohli9417 3 роки тому

    Keep up the good work 👏

  • @getthisechanelto100ksubs7
    @getthisechanelto100ksubs7 3 роки тому

    Traaaaassssshhhhhh

  • @nxgrs74
    @nxgrs74 3 роки тому

    1) By reflecting away 30% of ISR the albedo, which would not exist w/o the atmosphere/GHGs, makes the earth cooler than it would be without that atmosphere like that reflective panel set behind the windshield. Remove the atmosphere/GHGs and the earth would become much like the Moon, a barren rock with a 0.1 albedo, 20% more kJ/h, hot^3 on the lit side, cold^3 on the dark. Nikolov, Kramm (U of AK) and UCLA Diviner mission all tacitly agree. 2) the GHG up/down welling, “trapping”/”back” radiating/delaying/intercepting, 100 % efficient, perpetual warming loop requires "extra" energy which according to RGHE theory comes from 3) the terrestrial surface radiating that "extra" upwelling energy as a LWIR , 1.0 emissivity, ideal black body which 4) cannot happen because of the non-radiative, kinetic energy, heat transfer processes of the contiguous atmospheric molecules and as demonstrated by experiment, the gold standard of classical science: principia-scientific.org/debunking-the-greenhouse-gas-theory-with-a-boiling-water-pot/ 1 or 2 or 3 + 4 = 0 Greenhouse Effect + 0 Greenhouse gas warming + 0 man caused climate change/global warming. Version 2.0 082021

  • @nxgrs74
    @nxgrs74 3 роки тому

    1) By reflecting away 30% of ISR the albedo, which would not exist w/o the atmosphere/GHGs, makes the earth cooler than it would be without that atmosphere like that reflective panel set behind the windshield. Remove the atmosphere/GHGs and the earth would become much like the Moon, a barren rock with a 0.1 albedo, 20% more kJ/h, hot^3 on the lit side, cold^3 on the dark. Nikolov, Kramm (U of AK) and UCLA Diviner mission all tacitly agree. 2) the GHG up/down welling, “trapping”/”back” radiating/delaying/intercepting, 100 % efficient, perpetual warming loop requires "extra" energy which according to RGHE theory comes from 3) the terrestrial surface radiating that "extra" upwelling energy as a LWIR , 1.0 emissivity, ideal black body which 4) cannot happen because of the non-radiative, kinetic energy, heat transfer processes of the contiguous atmospheric molecules and as demonstrated by experiment, the gold standard of classical science: principia-scientific.org/debunking-the-greenhouse-gas-theory-with-a-boiling-water-pot/ 1 or 2 or 3 + 4 = 0 Greenhouse Effect + 0 Greenhouse gas warming + 0 man caused climate change/global warming. Version 2.0 082021

  • @thegreatawknin8872
    @thegreatawknin8872 4 роки тому

    You’re nothing but a Marxist rat

  • @almostpsych
    @almostpsych 4 роки тому

    @18:50 the text says quantitative, but Dr Beath says qualitative repeatedly. I'm pretty sure this is a typo, just pointing it out.

  • @scottwilson6314
    @scottwilson6314 4 роки тому

    Excellent description of basic procedures!

  • @MohammedAli-ou6hk
    @MohammedAli-ou6hk 6 років тому

    I miss macquarie uni :( Thank you for helping new students . Love from Saudi Arabia ❤️