Observatorio de seguridad en Bogotá : balance del año 2007. N0. 34 abril de 2008

Gestión del conocimiento

Resolución N° 34 ¿Tiene la Cámara de Comercio la competencia para pronunciarse respecto la calidad de accionista? ¿Cuál es el medio idóneo para verificar el quórum en una reunión de asamblea de accionistas?

Servicios registrales

Resolución N° 34 del 8 de marzo de 2007 ¿Cuáles son los criterios que tiene en cuenta la Cámara de Comercio para llevar a cabo el cobro de impuesto de registro en los casos de una fusión por absorción de sociedades?

Servicios registrales

The War, 9 February 1813 (vol. 1, no. 34) - Newspaper

Volumes of interest were published between 1812 and 1815 with articles about the War of 1812.

HG 336.70-336.80

Dark brown sediment with clasts ranging from small to large. Clasts are sub-angular to sub-rounded in shape. Larger tend to be more sub-rounded in this sample. Lineations and comet structures are present. Minor amounts of rotation structures can also be seen.

HG 34.70-34.85

Dark brown sediment with clasts that range from small to medium in size. The clasts were sub-angular to sub-rounded in shape. Lineations were abundant throughout the sample. It also contains some clay material and a few rotation structures.

GAO 34

Brown sediment with clasts ranging from small to large in a sandy matrix. Clast shape ranges from angular to rounded. The clasts are mainly well dispersed. Rotation structures are common in this sample, along with grain crushing. Some lineations can also be seen in this sample.

Certificate that Joseph Kingsmill, sheriff, has sold 3 ½ acres in Lot no. 34 in the 3rd Concession of Wainfleet to W. H. Dickson

Certificate that Joseph Kingsmill, sheriff, has sold 3 ½ acres in Lot no. 34 in the 3rd Concession of Wainfleet to W. H. Dickson, May 23, 1857.

Markovian Processes, Two-Sided Autoregressions and Finite-Sample Inference for Stationary and Nonstationary Autoregressive Processes.

In this paper, we develop finite-sample inference procedures for stationary and nonstationary autoregressive (AR) models. The method is based on special properties of Markov processes and a split-sample technique. The results on Markovian processes (intercalary independence and truncation) only require the existence of conditional densities. They are proved for possibly nonstationary and/or non-Gaussian multivariate Markov processes. In the context of a linear regression model with AR(1) errors, we show how these results can be used to simplify the distributional properties of the model by conditioning a subset of the data on the remaining observations. This transformation leads to a new model which has the form of a two-sided autoregression to which standard classical linear regression inference techniques can be applied. We show how to derive tests and confidence sets for the mean and/or autoregressive parameters of the model. We also develop a test on the order of an autoregression. We show that a combination of subsample-based inferences can improve the performance of the procedure. An application to U.S. domestic investment data illustrates the method.