- An Introduction to Stochastic Calculus lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Hit-or-Miss Dependence of Random Closed Sets Susan H. Xu
- PS7 key Stat 370 a) P-value = P( 2
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Section 5-2: Means of Two Popula-tions, Variance Known
- Tail Approximation of Value-at-Risk under Multivariate Regular Variation
- Sample Clouds, Point Processes and Random Sets lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Asymptotic Analysis of Multivariate Coherent Risks lih@math.wsu.edu
- Section 3-2: Random Events SAMPLE SPACE : A set of all possible outcomes
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Ch2. Data Summary & Presentation Univariate Data Summary
- PS5 key Stat 370 E )9(
- Section 4-8: Prediction & Tolerance Take a sample X1, . . . , Xn from a normal population
- PS6 key Stat 370 a) P-value = 2*P(t > 2.48): for degrees of freedom of 9 we obtain
- Section 3-5: Normal Distribution NORMAL density function N(, 2
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Section 4.6: Chi Square Test Hypotheses: H0 : 2
- Section 4.7: Population Proportion p Hypotheses: H0 : p = p0 VS H1 : p = p0.
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Section 6-2: Testing Hypotheses Consider a simple linear regression model
- PS1 key Stat 370 3-3. Continuous
- Tail Dependence for Heavy-Tailed Scale Mixtures of Multivariate Distributions
- Vine copulas with asymmetric tail dependence and applications to financial return data
- Tail Risk of Multivariate Regular Variation Third Revision, May 2010
- Tail Density Archimedean and t Copulas Tail Densities of Vines Concluding Remarks A tail density approach in extremal
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Section 3-9: Poisson Distribution Poisson distribution: Approximation of binomial dis-
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Section 3-13: Central Limit Theorem RANDOM SAMPLE: X1, X2, . . . , Xn are independent
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Section 4-3, 4-4: Hypothesis Testing Statistical hypothesis: A statement about the pa-
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Section 4.5: Variance 2 Unknown Hypotheses: H0 : = 0 VS H1 : = 0.
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Section 5-3: Means of Two Popula-tions, Variance Unknown
- Section 5-4: Paired t-Test Two populations with, respectively, unknown means
- Section 5-5: Variances Two populations with, respectively, unknown means
- Section 8-1 8-4: Statistical Process Control (SPC)
- Section 8-5: Control Charts for Indi-vidual Measurements
- Section 6-2: Simple Linear Regression X: Regressor or predictor.
- PS3 key Stat 370 The function is a probability mass function. All probabilities are nonnegative and sum
- Hypotheses Testing for 1. For random samples from a normal distribution with mean and standard deviation , we have,
- PS8 key Stat 370 d = 0.2769 sd = 0.1350, n = 9
- PS9 key Stat 370 a) chartx chartR
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Asymptotic Analysis of Multivariate Tail Conditional Expectations
- Section 3-4: Continuous Random Vari- Random Variables (RV): Denoted by capital letters,
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- PS10 key Stat 370 a) If the process uses 66.7% of the specification band, then 6 = 0.667(USL-LSL) then assume x since the process is centered
- Asymptotic Analysis of Multivariate Coherent Risks Multivariate coherent risks can be described as classes of portfolios consisting of extra capital
- Section 3-11: Random Vectors A vector of continuous random variables (X, Y ) is
- A Single Period Analysis of a Two-Echelon Inventory System with Dependent Supply Disruptions
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- An Introduction to Stochastic Calculus lih@math.wsu.edu
- Risk Assessment Coherent Risks: An Axiomatic Approach Relation with Cooperative Game Concluding Remarks Risk, Coherency and Cooperative Game
- Section 5-8: Analysis of Variance a treatments: a levels of the factor.
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Tail Approximation of Value-at-Risk under Multivariate Regular Variation
- Ch 7: Design of Experiments Controllable variables: temperature, pressure, feed
- Sec 8-7: Attribute Control Charts P Chart: Fraction-defective control chart, control
- Math/Stat 370: Engineering Statistics lih@math.wsu.edu
- Tail Distortion Risk and Its Asymptotic Analysis A distortion risk measure used in finance and insurance is defined as the expected
- Extremal Dependence of Copulas: A Tail Density August 2011
- Heavy Tails Tail Density Archimedean and t Copulas Tail Densities of Vines Concluding Remarks Tail Densities of Copulas and Extremal
- Workshop "Copulae in Mathematical and Quantitative Finance", 10-11 July 2012 and Short Course "Copulae Calibration in Theory
- Call for Papers Annals of Operations Research
- Asymptotic Analysis of Multivariate Tail Conditional Expectations
