Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
-
- 62-07 (1)
- 62G10 (1)
- 83C32 (1)
- Academic papers (1)
- Bayesian (1)
-
- Data analysis (1)
- Ebola (1)
- Econometrics (1)
- Event Data (1)
- HCI (1)
- Heterogeneity in treatment effects (1)
- Hierarchical Modeling (1)
- Hypothesis testing (1)
- Intrastate Conflict (1)
- Julia (1)
- Machine Learning (1)
- Meta-Analysis (1)
- Neural nets (1)
- Power Transition (1)
- Prediction (1)
- Program evaluation (1)
- Scientific Computing (1)
- Snapchat (1)
- Social Network Analysis (1)
- Statistical Software (1)
- Statistics (1)
- Stories (1)
- User experience (1)
- Video (1)
Articles 1 - 5 of 5
Full-Text Articles in Physical Sciences and Mathematics
Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer
Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer
HMC Senior Theses
Given the rise in the application of neural networks to all sorts of interesting problems, it seems natural to apply them to statistical tests. This senior thesis studies whether neural networks built to classify discrete circular probability distributions can outperform a class of well-known statistical tests for uniformity for discrete circular data that includes the Rayleigh Test1, the Watson Test2, and the Ajne Test3. Each neural network used is relatively small with no more than 3 layers: an input layer taking in discrete data sets on a circle, a hidden layer, and an output …
A Tacticians Guide To Conflict, Vol. 1: Advancing Explanations & Predictions Of Intrastate Conflict, Khaled Eid
A Tacticians Guide To Conflict, Vol. 1: Advancing Explanations & Predictions Of Intrastate Conflict, Khaled Eid
CGU Theses & Dissertations
Intrastate conflict is an ever-evolving problem – causes, explanation, and predictions are increasingly murky as traditional methods of analysis focus on structural issues as precursors of conflict. Often times these theories do not consider the underlying meso and micro dynamics that can provide vital insights into the phenomena. Tactical decision-makers are left using models that rely on highly aggregated, country level data to create proper courses of actions (COAs) to address or predict conflict. The shortcoming is that conflicts morph quite rapidly and structural variables can struggle capture such dynamic changes. To address this some tacticians are using big data …
On Cluster Robust Models, José Bayoán Santiago Calderón
On Cluster Robust Models, José Bayoán Santiago Calderón
CGU Theses & Dissertations
Cluster robust models are a kind of statistical models that attempt to estimate parameters considering potential heterogeneity in treatment effects. Absent heterogeneity in treatment effects, the partial and average treatment effect are the same. When heterogeneity in treatment effects occurs, the average treatment effect is a function of the various partial treatment effects and the composition of the population of interest. The first chapter explores the performance of common estimators as a function of the presence of heterogeneity in treatment effects and other characteristics that may influence their performance for estimating average treatment effects. The second chapter examines various approaches …
Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk
CMC Senior Theses
With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption.
To accelerate the growth of the creation of these research talks, I propose an alternative to video: …
Bayesian Hierarchical Meta-Analysis Of Asymptomatic Ebola Seroprevalence, Peter Brody-Moore
Bayesian Hierarchical Meta-Analysis Of Asymptomatic Ebola Seroprevalence, Peter Brody-Moore
CMC Senior Theses
The continued study of asymptomatic Ebolavirus infection is necessary to develop a more complete understanding of Ebola transmission dynamics. This paper conducts a meta-analysis of eight studies that measure seroprevalence (the number of subjects that test positive for anti-Ebolavirus antibodies in their blood) in subjects with household exposure or known case-contact with Ebola, but that have shown no symptoms. In our two random effects Bayesian hierarchical models, we find estimated seroprevalences of 8.76% and 9.72%, significantly higher than the 3.3% found by a previous meta-analysis of these eight studies. We also produce a variation of this meta-analysis where we exclude …