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The combined Poisson INMA(q) models for time series of counts X θ

The combined Poisson INMA(q) models for time series of counts X θ

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The asymptotic and finite sample simultaneous equations

The asymptotic and finite sample simultaneous equations

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Journal Club - Image Fusion

Journal Club - Image Fusion

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How to fulfill user needs – metadata, administrative data and processes

How to fulfill user needs – metadata, administrative data and processes

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Here - The Open University

Here - The Open University

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Goebell, PJ1, MÃ¼ller, L.2, LÃ¼ck, A.3, Overkamp, F.4

Goebell, PJ1, MÃ¼ller, L.2, LÃ¼ck, A.3, Overkamp, F.4

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B-tests: Low Variance Kernel Two-Sample Tests

B-tests: Low Variance Kernel Two-Sample Tests

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APSTA-GE 2995 Biostatistics I

APSTA-GE 2995 Biostatistics I

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Elizabeth Burmeister BN MSc Nurse Researcher SAMPLE SIZE: HOW MANY IS ENOUGH?

Elizabeth Burmeister BN MSc Nurse Researcher SAMPLE SIZE: HOW MANY IS ENOUGH?

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Choosing the sample size for equivalence trials

Choosing the sample size for equivalence trials

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CauseMap: fast inference of causality from complex time series

CauseMap: fast inference of causality from complex time series

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Constructing Confidence Intervals from a Ranked Set Sample Technical Report 783

Constructing Confidence Intervals from a Ranked Set Sample Technical Report 783

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CFA Level I Sample Examination for 2003 Candidates 120 Questions

CFA Level I Sample Examination for 2003 Candidates 120 Questions

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Adaptive background mixture models for real-time tracking

Adaptive background mixture models for real-time tracking

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effective study solutions to help them take their careers to the...

effective study solutions to help them take their careers to the...

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Dominant Local Binary Patterns for Texture Classification

Dominant Local Binary Patterns for Texture Classification

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Document

Document

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Two-Sample Designs Q560: Experimental Methods in Cognitive Science Lecture 9

Two-Sample Designs Q560: Experimental Methods in Cognitive Science Lecture 9

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The normal distribution assumption and other assumptions. I

The normal distribution assumption and other assumptions. I

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