Hydrological Interpretation of Basin Morphology

Completion Report OWRT Agreement No. 14-31-0001-5002 OWRT Project A-049-ALASHydrologic processes in a particular basin are governed by three groups of factors: input regimes of mass and energy, the nature of mass and energy transfer and transformation, and the biophysical characteristics of the basin. This third group provides the structural or morphological framework in which hydrologic processes are taking place and, as such, contributes significantly to the uniqueness of specific basin response.The work upon which this completion report is based was supported by funds provided by the U. S. Department of the Interior, Office of Water Research and Technology as authorized under the Water Resources Research Act of 1964, Public Law 88-379, as amended

Hydrometeorological Literature Review for the Delta-Clearwater Creek Area

Completion Report State of Alaska Department of Natural Resources Reimbursable Service Agreement Dated August 19, 1977Phase One of this study consists of a search for existing hydrometeorological data or other information relevant to environmental baseline studies of the Delta-Clearwater Creek agricultural development project. A general summary of this literature search is presented below; a detailed annotated bibliography immediately follows the summary. Phase Two consists initially of a preliminary analysis, based on existing information, of the local water budget, the groundwater regime, and the potential for transport of agricultural chemicals into the water system. Finally, evaluation and comments on the adequacy or sufficiency of existing data and recommendation for future work are made. Selected charts, diagrams, or tables of data have been included in the text where such information is relevant, but not voluminous.This project and report were supported through a contract from the State of Alaska, Department of Natural Resources

The R Commander: A Basic-Statistics Graphical User Interface to R

Unlike S-PLUS, R does not incorporate a statistical graphical user interface (GUI), but it does include tools for building GUIs. Based on the tcltk package (which furnishes an interface to the Tcl/Tk GUI toolkit), the Rcmdr package provides a basic-statistics graphical user interface to R called the "R Commander." The design objectives of the R Commander were as follows: to support, through an easy-to-use, extensible, cross-platform GUI, the statistical functionality required for a basic-statistics course (though its current functionality has grown to include support for linear and generalized-linear models, and other more advanced features); to make it relatively difficult to do unreasonable things; and to render visible the relationship between choices made in the GUI and the R commands that they generate. The R Commander uses a simple and familiar menu/dialog-box interface. Top-level menus include File, Edit, Data, Statistics, Graphs, Models, Distributions, Tools, and Help, with the complete menu tree given in the paper. Each dialog box includes a Help button, which leads to a relevant help page. Menu and dialog-box selections generate R commands, which are recorded in a script window and are echoed, along with output, to an output window. The script window also provides the ability to edit, enter, and re-execute commands. Error messages, warnings, and some other information appear in a separate messages window. Data sets in the R Commander are simply R data frames, and can be read from attached packages or imported from files. Although several data frames may reside in memory, only one is "active" at any given time. There may also be an active statistical model (e.g., an R lm or glm ob ject). The purpose of this paper is to introduce and describe the use of the R Commander GUI; to describe the design and development of the R Commander; and to explain how the R Commander GUI can be extended. The second part of the paper (following a brief introduction) can serve as an introductory guide for students who will use the R Commander.

Effect Displays in R for Generalised Linear Models

This paper describes the implementation in R of a method for tabular or graphical display of terms in a complex generalised linear model. By complex, I mean a model that contains terms related by marginality or hierarchy, such as polynomial terms, or main effects and interactions. I call these tables or graphs effect displays. Effect displays are constructed by identifying high-order terms in a generalised linear model. Fitted values under the model are computed for each such term. The lower-order "relatives" of a high-order term (e.g., main effects marginal to an interaction) are absorbed into the term, allowing the predictors appearing in the high-order term to range over their values. The values of other predictors are fixed at typical values: for example, a covariate could be fixed at its mean or median, a factor at its proportional distribution in the data, or to equal proportions in its several levels. Variations of effect displays are also described, including representation of terms higher-order to any appearing in the model.

Effect Displays in R for Multinomial and Proportional-Odds Logit Models: Extensions to the effects Package

Based on recent work by Fox and Andersen (2006), this paper describes substantial extensions to the effects package for R to construct effect displays for multinomial and proportional-odds logit models. The package previously was limited to linear and generalized linear models. Effect displays are tabular and graphical representations of terms - typically high-order terms - in a statistical model. For polytomous logit models, effect displays depict fitted category probabilities under the model, and can include point-wise confidence envelopes for the effects. The construction of effect displays by functions in the effects package is essentially automatic. The package provides several kinds of displays for polytomous logit models.

Soil Composition

Soil is essential for life on Earth. It is needed for food, air, clothing and so much more. Discussion topics include the terms 'soil', 'dirt', and 'sediment', factors affecting the formation of soils, soil horizons, and the twelve orders of soils. In a hands-on activity, students will collect soil samples from three different locations, use online resources to determine texture and particle makeup, and record their observations. Educational levels: Undergraduate lower division, High school