No description available.

A forest inventory was made by a two-man team in the Emory oak (Quercus emoryi) woodlands, near the Huachuca Mountains, in southeastern Arizona. Two plot sizes, 1/10th, and 1/25th hectare, and three basal area factors, 2, 4 and 6 (square meters per hectare) were used. Tree tally time was recorded, but the travelling time between plots was not recorded. Total number of trees, total basal area, and total volume of trees per hectare were measured, summarized, and analyzed. Significant differences were noted between plot sampling and point sampling. Results suggested that with plot sampling, 1/25th hectare plot was more efficient than 1/10th hectare plot for all measures of forest densities. With point sampling, basal area factor 6 had the highest relative sampling efficiency in terms of trees per hectare. Basal area factor 2 had the highest relative sampling efficiency in terms of basal area and volume per hectare. From this information, more efficient forest inventories of the Emory oak woodlands can be designed.

No description available.

No description available.

Eucalypt trees are one of tree species used for the manufacturing of papers in South Africa. The manufacturing of paper consists of cooking the wood with chemicals until obtaining a pulp. The wood is made of different cells. The shape and structure of these cells, called wood anatomical characteristics are important for the quality of paper. In addition, the anatomical characteristics of wood are influenced by environmental factors like climatic factors, soil compositions etc…. In this study we investigated the effects of the climatic factors (temperature, rainfall, solar radiation, relative humidity, and wind speed) on wood anatomical characteristics of two Eucalyptus clones, a GC (Eucalyptus grandis × camuldulensis) and a GU (Eucalyptus grandis × urophylla). Nine trees per clone have been selected. Two sets of data have been collected for this study. The first set of data was eleven anatomical characteristics of the wood formed daily over a period of five years. The second set of data was the daily measurement of temperature, rainfall, solar radiation, relative humidity and wind speed in the experimental area. Wood is made of two kinds of cell, the fibres and the vessels. The fibres are used for the strength and support of the tree and the vessels for the nutrition. Eleven characteristics related to those cells have been measured (diameter, wall thickness, frequency). These characteristics are highly correlated. To reduce the number of response variables, the principal component analysis was used and the first four principal components accounts for about 95% of the total variation. Based on the weights associated with each component the first four principal components were labelled as vessel dimension (VD), fibre dimension (FD), fibre wall (FW) and vessel frequency (VF). The longitudinal linear mixed model with age, season, temperature, rainfall, solar radiation, relative humidity and wind speed as the fixed effects factors and tree as random effect factor was fitted to the data. From time series modelling result, lagged order of climatic variables were identified and these lagged climatic variables were included in the model. To account for the physical characteristic of the trees we included the effect of diameter at breast height, stem radius, daily radial increment, and the suppression or dominance of the tree in the model. It was found that wood anatomical characteristics of the two clones were more affected by climatic variables when the tree was on juvenile stage as compared to mature stage. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.

This thesis presents three models of asset pricing involving non-competitive behavior and asymmetric information. In the first model, a risk averse investor with private information about dividends trades shares over an infinite time horizon with risk neutral uninformed agents. The informed investor trades strategically in equilibrium. The second model also involves an infinite time horizon, but all agents are risk averse and equally informed about dividends. Non-competitive behavior is exogenously specified; price takers trade shares with a strategic investor who accounts for the effects of her trades on the stock price. In this case, an endogenous information asymmetry arises in equilibrium. Closed form equilibria are derived for both models and implications for price dynamics are explored. While the first model constitutes a new extension of the multiperiod Kyle model of insider trading, the second model generates more interesting price dynamics. If the strategic investor manages a large mutual fund, significant risk premia and price volatility may arise in equilibrium. In fact, if mutual fund participation is sufficiently widespread, multiple equilibria may exist. The third model extends the multiperiod Kyle model to a case where the insider observes a noisy signal of the stock's terminal liquidation value. An equilibrium much like Kyle's is derived. Price tends toward value over time, and stock price volatility depends on both the drift and volatility of the insider's private signal. Like the Kyle model, the insider's trading activity leaves no detectable trace in trading volume, expected returns, or price volatility.

No description available.

No description available.

Time-series data that reflect a periodic pattern are often used in psychology. In personality psychology, Brown and Moskowitz (1998) used spectral analysis to study whether fluctuations in the expression of four interpersonal behaviors show a cyclical pattern. Spline smoothing had also been used in the past to track the non-periodic trend, but no research has yet been done that combines spectral analysis and spline smoothing. The present thesis describes a new model which combines these two techniques to capture both periodic and non-periodic trends in the data. / The new model is then applied to Brown and Moskowitz's time-series data to investigate the long-term evolution to the four interpersonal behaviors, and to the GDP data to examine the periodic and non-periodic pattern for the GDP values of the 16 countries. Finally, the extent to which the model is accurate is tested using simulated data.

A new approach to structural equation modeling based on so-called extended redundancy analysis (ERA) is proposed. In ERA, latent variables are obtained as exact linear combinations of observed variables, and model parameters are estimated by consistently minimizing a single criterion. As a result, the method can avoid limitations of covariance structure analysis (e.g., stringent distributional assumptions, improper solutions, and factor score indeterminacy) in addition to those of partial least squares (e.g., the lack of a global optimization procedure). The method is simple yet versatile enough to fit more complex models; e.g., those with higher-order latent variables and direct effects of observed variables. It can also fit a model to more than one sample simultaneously. Other relevant topics are also discussed, including data transformations, missing data, metric matrices, robust estimation, and efficient estimation. Examples are given to illustrate the proposed method.